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arXivU Wisconsin–Madison New York Stanford RL for LLMs

Sharpening Tax in Post-Training

Post-training sharpens base model behaviors at the cost of solution coverage, introducing a quantifiable "Sharpening Tax"; a posterior-tempered group sampler reduces this tax while boosting accuracy.

Changdae Oh, Qi Zeng, Qi Qi, Andrey Zhmoginov and 6 more

Published Oct 1, 2026 · 0 citations · ▲ 102 on Hugging Face · Code ★ 25

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arXivGoogle U North Carolina Health Care Stanford Washington University in St. Lou LLM agents & planning

RRSI: Regularized Recursive Self-Improvement of Agent Harnesses

RRSI regularizes recursive agent harness self-improvement via annealed edit budgets, trajectory exploration, and critical selection to boost out-of-distribution performance and reduce token use. It improves up to 14.1 points in-distribution and 4.7 points out-of-distribution while cutting policy tok

Peng Xia, Rujun Han, Zifeng Wang, Yanfei Chen and 10 more

Published Sep 21, 2026 · 0 citations · ▲ 222 on Hugging Face · Code ★ 1,293

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arXivU Washington Stanford LLM pretraining & scaling laws

Scaling Participation in Modular AI Systems

Modular participatory AI combines small stakeholder-trained models into compositional systems that outperform monolithic LLMs by up to 15.4% and exhibit emergent collaborative capabilities.

Shangbin Feng, Yike Wang, Weijia Shi, Luke Zettlemoyer and 2 more

Published Jun 5, 2026 · 0 citations

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67%Highly rated

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ACL 2026U Washington New York Massachusetts Institute of Techn Stanford Test-time compute

When One LLM Drools, Multi-LLM Collaboration Rules

Multi-LLM collaboration outperforms single LLM reasoning on tasks where individual models fail, demonstrating collective rule over solo drooling.

Shangbin Feng, Wenxuan Ding, Alisa Liu, Zifeng Wang and 9 more

Published 2026 · 1 citation

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70%Highly rated

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ACL 2025U Washington Stanford Ethics & social impact

Biased LLMs can Influence Political Decision-Making

Biased LLMs influence political decision-making, altering judgments and choices in simulated policy scenarios with measurable partisan effects.

Jillian Fisher, Shangbin Feng, Robert Aron, Thomas Richardson and 5 more

Published 2025 · 13 citations

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arXivU California, Berkeley Stanford U California San Diego Efficient inference & serving

Efficient Memory Management for Large Language Model Serving with PagedAttention

PagedAttention applies OS virtual memory and paging to LLM key-value caches, reducing waste and duplication to boost vLLM throughput 2-4x over existing systems.

Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng and 5 more

Published Sep 12, 2023 · 50 citations · ▲ 76 on Hugging Face · Code ★ 86,094

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NeurIPS 2026Stanford Molecules & drug discovery

GlycoGen: Crystallizing Flows for De Novo Glycan Structure Prediction

Romain Lacombe

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Toyota Technological Institute a RL for LLMs

A Theoretical Framework for Self-Play Theorem Proving Algorithms

Thomas Chen, Zhiyuan Li

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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57%Worth a look

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NeurIPS 2026OralUniversitys of Waterloo U Waterloo Stanford Yale Semi- & weakly supervised learning

Surprises in Proper Positive-Only Learning

Shai Ben-David, Farnam Mansouri, Anay Mehrotra, Manolis Zampetakis

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Semi- & weakly supervised learning

Partially Performative Prediction

Jaewook Lee, Tijana Zrnic

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Swiss Federal Institute of Techn Goodfire Adversarial robustness

Shifting the Gradient: Understanding How Defensive Training Methods Protect Language Model Integrity

Satchel Grant, Victor Gillioz, Jake Ward, Tom McGrath

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford University, Department Stanford Stanford Bayesian & probabilistic methods

An exact information theory of generalization phase transitions in Bayesian diffusion models

Henry Hunt, Mason Kamb, Surya Ganguli

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Carnegie Mellon Stanford Learning theory

Bentkus-type asymptotic e-values

Diego Martinez Taboada, Ben Chugg, Aaditya Ramdas

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Yale Stanford LLM reasoning & chain of thought

Reasoning with Sampling: Cutting at Decision Points

Felix Zhou, Anay Mehrotra, Quanquan C Liu

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Peking ByteDance Stanford The Chinese University of Hong K Massachusetts Institute of Techn Video generation

Spatially-Grounded Long Video Generation with Self Geometry Forcing

Chenguo Lin, Panwang Pan, Bowen Xue, Ruijie Lu and 4 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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69%Highly rated

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NeurIPS 2026Stanford Stanford Stanford University / Virtue AI Alignment & preference optimization

Behaving Better, Thinking Worse: Sycophancy Across Post-Training Stages

Sonnet Xu, Kritika Singh, Sheharbano Jafry, Roxana Daneshjou and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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67%Highly rated

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NeurIPS 2026Harvard Stanford Jilin ByteDance Inc.Vision-language models

Render Structure Uncertainty for HTML Repair in MLLM-based UI-to-Code Generation

Haoran Ma, Jiechao Gao, Shisong Tang, bing han and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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57%Worth a look

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NeurIPS 2026Stanford Apple U Oxford U Texas at Austin Harvard Fairness & bias

Multigroup Fairness and Omniprediction: Separations and Equivalences

Sílvia Casacuberta, Parikshit Gopalan, Varun Kanade, Omer Reingold and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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45%Niche pick

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NeurIPS 2026d_model ML & Alignment Theory Schola Stanford MATS Research Google DeepMind Deep RL

Gradient Routing Localizes and Removes Unintended Behaviors in RL

Jake Ward, Shawn Hu, Aria Wong, Nathan Hu and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Maryland, College Park Stanford Bar-Ilan Goodfire LLM pretraining & scaling laws

Pretraining Data Statistics Shape the Phases of Learning Entity Comparison in Language Models

Yik S Chan, Jing Huang, Yanai Elazar, Atticus Geiger

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Efficient attention & state-space models

Parallel Broyden methods for efficiently evaluating nonlinear state space models

Ian Christopher Tanoh, Scott Linderman

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Tsinghua The University of Sydney Stanford Baichuan Multimodal hallucination

VIGOR: Visual Gain Ordering for Hallucination Mitigation in Multimodal Discrete Diffusion Language Models

Junzhe Chen, Tian Qin, Eugenie Shi, Tianshu Zhang and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford U California, Berkeley UC Berkeley Materials & chemistry

CME–SpectrumBench: Can LLMs Analyze Condensed Matter Spectral Data?

Jin Gene Wong, Anjney Midha, Joseph Tennyson, Wei-Lin Chiang and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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57%Worth a look

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NeurIPS 2026Purdue Stanford Michigan State Purdue University RL for LLMs

$f$-GRPO & Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment

Rajdeep Haldar, Lantao Mei, Guang Lin, Yue XING and 1 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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45%Niche pick

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NeurIPS 2026Hong Kong University of Science Ant Group Ant Research Stanford Pose & motion

PosePlaner: Denoising Any Feedforward Pose Predictor from Pairwise Planar Geometry

Yihang Chen, Bin Tan, Yujun Shen, Yinghao Xu and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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69%Highly rated

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NeurIPS 2026OralThe University of Tokyo The University of Tokyo & RI Waseda University, Japan Waseda RIKEN Agent benchmarks & environments

Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations

Junjue Wang, Weihao Xuan, Heli Qi, Pengyu Dai and 6 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Computer Science Department, Sta SAP SE Apple &amp; University of Wa Stanford University/Pinterest Graphs & LLMs

Large-Scale Pretraining unlocks Few-Shot Prediction for Relational Data

Rishabh Ranjan, Vignesh Kothapalli, Harshvardhan Agarwal, Charilaos Kanatsoulis and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Stanford Google Brain Efficient inference & serving

Accelerating the Inference Era with AI-Driven, Globally Optimized HW/SW Co-Design

Miria Feng, Fangzhao Zhang, Adrian G Lafuente, Mert Pilanci and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Tsinghua University, Tsinghua Ant Group Hong Kong University of Science Ant Research Stanford Video generation

Persistent Planar Memory for Video World Models

Yuze He, Bin Tan, Zelin Gao, Yujun Shen and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ustc.edu.cn U Science and Technology of Chin U Technology Sydney; Data61, CSI Mohamed bin Zayed University of Shanghai AI Laboratory Navigation & SLAM

Seeing Together, Acting Apart: Shared Environmental Understanding for Multi-Robot Navigation

haihong hao, Lei Chen, Mingfei Han, Dong An and 6 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Stanford University / Virtue AI Efficient & distributed training

Is Backpropagation Optimal? When Synthetic Gradients Improve Sample Efficiency

Yibo Jacky Zhang, Zeyu Tang, Sanmi Koyejo

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026U Science and Technology of Chin Stanford Jilin Image recognition

U-MOF: Uncertainty-Guided Parameter-Efficient Multi-Objective Fine-Tuning for Long-Tailed Recognition

Yuan Dong, Di Wu, Zhe Zhao, Liheng Yu and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Science and Technology of Chin Stanford Jilin Image recognition

BasicLT: Basic-Level Abstraction and Selective Differentiation for Long-Tailed Recognition

Yuan Dong, Di Wu, Zhe Zhao, Liheng Yu and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026National University of Singapore Department of Computer Science a Nanjing Xi'an University of Posts a Institute of Automation, Chinese Molecules & drug discovery

Pareto Preference Optimization for Structure- and Stability-Aware RNA Inverse Folding

Minghao Sun, Hanqun Cao, Zhou Zhang, Chen Wei and 9 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Google Deepmind Tilde Research / Stanford Tilde Research Parameter-efficient fine-tuning

PreFT: Prefill-only finetuning for inference efficiency

Andrew Lanpouthakoun, Aryaman Arora, Zhengxuan Wu, Dhruv Pai and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Microsoft Research / UIUC MPI for Intelligent Systems, Tüb Max Planck Institute for Intelli Stanford MIT LLM evaluation & benchmarks

AI Construct Lexis: An Ontology of the Hidden Assumptions in AI Evaluation

Olawale Salaudeen, Florian E. Dorner, Tom Sühr, Sang Truong and 12 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Texas, Austin Stanford Stanford Video generation

Recreating Video Arenas via Automated Preference Scoring

Yue Zhao, Aniket Gupta, Juze Zhang, Tiange Xiang and 4 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026OralU Tübingen Stanford Eberhard-Karls-Universität Tübin Tübingen AI Center, University o University College London, Unive Computational neuroscience

Evaluating Neural Data Tokenizers: A Framework for Assessing Learned Representations of Spiking Activity

Federico D&#x27;Agostino, Alex Gilbert, Susanne Keller, Jaivardhan Kapoor and 16 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford U British Columbia, Google Stanford University / Virtue AI LLM evaluation & benchmarks

Strategic Evaluation: Incentivizing AI Capability Coverage with Private Benchmarks

Sang Truong, Serena Wang, Nick Haber, Sanmi Koyejo

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Microsoft U Washington Stanford Research, Microsoft PUC-RIO RL for LLMs

Multi-Turn RL Makes Small Language Model Competitive for Optimization Modeling

Xinzhi Zhang, Zeyi Chen, Humishka Zope, Hugo Barbalho and 5 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford Uber Vision-language models

Rethinking Contrastive Targets in Radiology Language-Image Pretraining

Yunhe Gao, Ashwin Kumar, Jiaming Liu, Chong Wang and 7 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford U Hong Kong U Cambridge U the Chinese Academy of Science Vision-language models

Anchoring LLM-based Chest X-ray Report Generation via Diffusion Language Planning

Jiechao Gao, Chang Liu, Yuandong Pan, Ying Liu and 1 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Institute of Science and Technol Stanford ETH Zurich Google Brain LLM pretraining & scaling laws

Speculative Self-Distillation enables Efficient Knowledge Internalization

Shayan Talaei, Agam Bhatia, Arshia Soltani Moakhar, Jonas Hübotter and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Vision-language models

Learning to See Through Language: An Exploration of Language Modeling's Effect on Visual Representations

Mark Endo, Shiye Su, Yuhui Zhang, Serena Yeung-Levy

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford U Cambridge Stanford AI oversight & deception

Position: AI Development Should Prioritize Cognitive Security

Batu El, Shiye Su, Aneesh Pappu, Peggy Yin and 5 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightStanford U Washington RL for LLMs

Rethinking Visual Reasoning in Text-to-Image Reward Modeling

Shiye Su, Xiaohan Wang, Ludwig Schmidt, Serena Yeung-Levy

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U British Columbia Zhejiang Stanford Vector Institute UBC | Vector Institute | Google Speech synthesis

RVCBench: Benchmarking Robustness of Voice Cloning Across Modern Audio Generation Models

Ruinan Jin, Xinting Liao, Hanlin Yu, Deval Pandya and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford U Minnesota - Twin Cities U Wisconsin - Madison Johns Hopkins Texas A&M University - Colle 3D generation

AnaDiffusion: Anatomically Compositional Latent Diffusion for Controllable 3D Brain MRI Generation

Tracy Han, Lulin Liu, Bangya Liu, Yuanhao Cai and 7 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Northeastern Stanford Stanford Khoury College of Computer Scien LLM agents & planning

Shepherd: A Runtime Substrate Empowering Meta-Agents with a Formalized Execution Trace

Simon Yu, Derek Chong, Ananjan Nandi, Dilara Soylu and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Pose & motion

DopplerWild: A Doppler Dataset and Benchmark for Human Kinematic Understanding in the Wild

Shubo Yang, Aaron Wang, Narayan Schütz, Jida Zhang and 4 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026U California, Berkeley Peking U Science and Technology of Chin Carnegie Mellon Stanford Software engineering agents

Verify0: Can AI Agents Build Formally Verified Software Repositories?

Zhe Ye, Hantao Lou, Yuechun Sun, Peiyang Song and 7 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Modal/Harvard Stanford Harvard Thinking Machines Lab, Stanford Columbia ML systems & compilers

Hawkeye: Hardware-Aware GPU Kernel Optimization with Minimal Supervision

Arya Tschand, Kesavan Ramakrishnan, Alexander Ingare, Simon Guo and 5 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Princeton Harvard UIUC Facebook Code generation

ProgramBench: Can Language Models Rebuild Programs From Scratch?

John Yang, Kilian Lieret, Jeffrey Ma, Parth Thakkar and 8 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Stanford U Maryland, College Park Imperial College London Google DeepMind Proteins

Plausible Biomolecular Structure Prediction via Physics-informed Reinforcement Learning

Tai Dang, Hieu Tran, Long-Hung Pham, Sang Truong and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Stanford Vision-language models

Multimodal AI Detection In Two Words

Daniel Fein, Arpita Singhal, Maneesh Agrawala, Maty Bohacek

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026University College London, Unive Gatsby Unit, UCL Stanford Deep learning theory

How are linear representations learned? Exact solutions to the dynamics of abstraction

William W Yang, Peter E Latham, Andrew Saxe

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Percepta Cornell Representation & contrastive learning

Refactoring Code Through Library Design

Žiga Kovačič, Justin Chiu, Celine Lee, Wenting Zhao and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Diffusion models

Order-Marginalized Scoring for Masked Diffusion Models

Arthur Deng, Sebastian Thrun

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford U Washington U Washington; Meta Carnegie Mellon Stanford University/Pinterest Unified multimodal models

M*: A Modular, Extensible, Serving System for Multimodal Models

Atindra Jha, Naomi Sagan, Keisuke Kamahori, Irmak Sivgin and 8 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Universitat Politècnica de Catal Stanford Universitat Pompeu Fabra Universidad Politécnica de Catal U California, Berkeley Datasets & benchmarks

TabBioMed: A Large-Scale Benchmark for Biomedical Tabular Learning

Pau Mateo Bernadó, Saivenkata Nagavyjayanthi Polapragada, Pol Arbiol Rakuljic, Laia M Pladevall and 7 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026SpotlightStanford LLM reasoning & chain of thought

Large language models suffer from a curse of ambiguity

Nicolas Zucchet, Hyun Dong Lee, Scott Linderman

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Stanford Biosignals & wearables

Online Bayesian Recalibration of Brain–Computer Interfaces with Language Model Potentials

Noah Cowan, Scott Linderman

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Proxy Foods U Piraeus Proxy Foods Inc.Food System Innovations Proteins

Expert-guided Bayesian optimization for sustainable protein formulation

Anna Thomas, Georgios Zaverdinos, Petros Mandalis, Andreas Orfanoudakis and 8 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Chalmers University of Technolog FU Berlin Stanford U Copenhagen Molecules & drug discovery

Looking Under the Streetlight: Evaluation in Generative Molecular Dynamics

Simon Olsson, Frank Noe, Grant Rotskoff, Kresten Lindorff-Larsen

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U Michigan - Ann Arbor Stanford / UT-Austin Ohio State University, Columbus Stanford Massachusetts Institute of Techn LLM agents & planning

Agent-Native Research Artifacts

Jiachen Liu, Jiaxin Pei, Jintao Huang, Chenglei Si and 33 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford Peking Mechanistic interpretability

Do Latent-CoT Models Think Step-by-Step? A Mechanistic Study on Sequential Reasoning Tasks

Jia Liang, Liangming Pan

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford Panasonic Panasonic Holdings Corporation Panasonic Corporation Salesforce AI Research 3D vision & reconstruction

EgoMo3R: Joint Egocentric Motion and Scene Reconstruction

Chaitanya Patel, Yusuke Kato, Rin Takahira, Kazuki Kozuka and 2 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford Stanford University / Virtue AI Machine unlearning

What to Forget in Unlearning? Forget Set Curation for Language Models

Animesh Jha, Arpandeep Khatua, Youssef Allouah, Sanmi Koyejo

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026CeMM & Medical University of Mines ParisTech CeMM Research Center for Molecul Stanford Genomics & single-cell

Designing Cell-Type-Specific Regulatory DNA with Guided Discrete Diffusion

Animesh Awasthi, Martin Stoll, Raphael Bednarsky, Moritz Schaefer and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Carnegie Mellon AI oversight & deception

Corrupted Plans, Clean Traces: What Planning-Execution Decoupling Reveals About CoT Monitoring

Keertana Chidambaram, Andrew Ilyas, Vasilis Syrgkanis

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026KTH Royal Institute of Technolog Harvard Mistral AI Stanford Cambridge, Alan Turing Institute Reward models & LLM-as-a-judge

A Matter of Interest: Understanding Interestingness Judgments of Math Problems in Humans and Language Models

Shubhra Mishra, Yuka Machino, Gabriel Poesia, Albert Q. Jiang and 8 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Broadmetrics Stanford University / Virtue AI Domain adaptation

Benchmarks as Measurement Instruments: Quantifying Signal and Noise for More Efficient AI Evaluations Under Distribution Shift

Michael Hardy, Anka Reuel-Lamparth, Jodi Casabianca, Hansol Lee and 3 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Harvard AIGCode Lenovo Group Limited U Michigan - Ann Arbor Stanford Code generation

Phase-wise MLLM Tuning for Multi-framework WebUI Code Generation

Haoran Ma, Linxiao Li, Chenyue Wang, Haochen Sui and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026AIGCode Harvard Lenovo Group Limited Tsinghua U Michigan - Ann Arbor Code generation

Toward Executable Multi-framework Front-end Code Generation with Self-Correction

Linxiao Li, Haoran Ma, Chenyue Wang, Jiaye Lin and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Carnegie Mellon CMU, Carnegie Mellon U Washington Stanford Proteins

DUIL: Deep Unsupervised Inverse Learning for in situ Macromolecular Morphology Identification

Mostofa Rafid Uddin, Seonghui Min, Mahek Vora, Qifeng Wu and 2 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford Fremont Unified School District Stanford MIT/Google Text-to-image

Characterizing the Aesthetic Defaults of Generative Image Models

Maty Bohacek, Raina Panda, Daniel Fein, Arpita Singhal and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026University College London, Unive Concord AI Stanford Efficient & distributed training

An Analytical Model of Compute-limited Multistage Training Pipelines

Nishil Patel, Jin Hwa Lee, Basile Confavreux, Andrew Saxe

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Massachusetts Institute of Techn U California, Berkeley MIT In-context learning & prompting

Prompt-Driven Exploration

Sunshine Jiang, John Marangola, David Zhang, Raghuram Kowdeed and 5 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026U Illinois at Urbana Champaign U Illinois Champaign-Urbana Stanford U Illinois at Urbana-Champaign U Illinois Urbana Champaign Test-time compute

Training Agent to Scale Inference-Time Reasoning

Yunzhe Qi, Sirui Chen, Jiaru Zou, Yanjun Zhao and 2 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford U California, Berkeley U California, Los Angeles Unified multimodal models

PM1: A Multimodal Foundation Model for Genomes, Phenotypes, and Images at Biobank Scale

Christophe Thomassin, Marçal Comajoan Cara, Margarita Geleta, David Bonet and 3 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford Institute of Science and Technol Ecole des Mines Technion - Israel Institute of T Physics-informed ML & PDEs

Symplectic Reck: In-Situ Learning of Gaussian Quantum Operations

Janet Zhong, Renwen Yu, Charles Roques-Carmes, Paul-Alexis MOR and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026City City University of Hong Kong Tsinghua Stanford Multimodal reasoning

SynGeo: Synergizing Seeing and Proving through Revisable Geometric States

Tianyi Xu, Liu Yang, Wenjun GAO, Junyu Ou and 4 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Northeastern Stanford Amazon Amazon Science Microsoft Synthetic data

Firefly: Illuminating Verified Real-world Tool Call Data Generation

Yuxuan Lu, Ziyi Wang, Yingzhou Lu, Yisi Sang and 11 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026SpotlightStanford Dartmouth College U California Los Angeles Mechanistic interpretability

A Mechanistic Investigation of Theory of Mind in a Large Language Model

Idil K Sahin, Steven M Frankland, Taylor Webb

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Rutgers Stanford U Texas at Arlington NYU Langone Medical imaging

UniPro: Unified Multi-Mode Medical Image Segmentation from 2D Images to 3D Volumes via Propagation

Bangwei Guo, Yunhe Gao, Meng Ye, Yang Zhou and 4 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Wellcome Sanger Institute / Univ Sanger institute Wellcome Sanger Institute wellcome sanger institute Newcastle University, UK Genomics & single-cell

MUSS: A Multi-scale and Sequence-based Model for Single-cell Gene Regulation

Kangjie Zheng, Amirhossein Vahidi, Liying Jin, Joseph Clarke and 6 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Carnegie Mellon U Michigan - Ann Arbor U Michigan Model OS Stanford LLM pretraining & scaling laws

Witness Overlap: Directional Provenance Inside Open-Weight Model Families

Siyuan Li, Haoxuan Zeng, Xin Luo, Fernando Jia and 5 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Cornell Department of Computer Science, Stanford Cornell University / ASAPP Resea LLM pretraining & scaling laws

Language Denoising Objectives Extend the Value of Limited Data

Justin Lovelace, Christian Belardi, Srivatsa R Kundurthy, Shriya Sudhakar and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford Test-time compute

Selected-Tail Reliability in Verifier-Guided Best-of-$N$ Inference

Teresa Zhang

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford U Southern California Causal inference

Statistical Inference in Causal Partial Identification under Smooth Densities

Sirui Lin, Zijun Gao, Jose Blanchet, Peter W Glynn

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Stanford Together AI Google Brain Stanford On-device ML

Intelligence per Watt: Measuring Intelligence Efficiency of Local AI

Proposing intelligence per watt to evaluate local LLM inference, the study finds local models answer 88.7% of queries with 5.3x efficiency gains since 2023 but remain 1.4x less efficient than cloud accelerators.

Jon Saad-Falcon, Avanika Narayan, Hakki Akengin, J. W Griffin and 10 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 17 on Hugging Face · Code ★ 95

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NeurIPS 2026KTH, TRATON Cornell Stanford Vision-language models

Bridging Structure and Language: Graph-Based Visual Reasoning for Autonomous Road Understanding

CRS unites geometric road graphs with open vocabulary semantics to generate structured reasoning data, showing small models trained on few scenes surpass large vision-language models at structured road reasoning.

Lena Wild, Katie Luo, Marco Pavone

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Time series classification & imputation

Closing the Approximation Gap in Simulation-free Latent SDEs

Simulation-free latent SDE inference restricts approximate posteriors and degrades learning, but Helmholtz-SDE closes the gap by optimizing over compatible path laws to match simulation-based accuracy at lower cost.

Henry Smith, Brian L Trippe, Scott Linderman

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Efficient inference & serving

Flash-SD-KDE: Accelerating SD-KDE with Tensor Cores

Reordering SD-KDE to expose matrix multiplications enables Tensor Core GPU acceleration, yielding up to 47x faster score-debiased density estimation at million-sample scales.

Elliot Epstein, Rajat Vadiraj Dwaraknath, John Winnicki

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Massachusetts General Hospital, Zendesk Shanghai University of Finance a Moscow Independent Research Inst Stanford Multimodal reasoning

MAEB: Massive Audio Embedding Benchmark

MAEB benchmarks 30 audio tasks across 100+ languages, finding no single model dominates and acoustic and linguistic skills trade off.

Adnan E Assadi, Isaac Chung, Chenghao Xiao, Roman Solomatin and 14 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 25 on Hugging Face

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NeurIPS 2026Stanford Privacy

Shuffle and Joint Differential Privacy for Generalized Linear Contextual Bandits

Algorithms for generalized linear contextual bandits achieve shuffle-DP regret scaling as $\tilde O(d^{3/2}\sqrt{T}/\sqrt{\varepsilon})$ and joint-DP regret matching non-private rates plus additive privacy corrections without spectral assumptions.

Sahasrajit Sarmasarkar

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U Illinois, Chicago Salesforce AI Research Salesforce Research SalesForce.com Recursive Superintelligence LLM evaluation & benchmarks

BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces

BehaviorBench evaluates personalized decision modeling using real-world wallet traces across belief and trade prediction tasks, showing personalization improves beliefs more than trades and reveals model failure modes.

Liangwei Yang, Jielin Qiu, Zixiang Chen, Ming Zhu and 8 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford Stanford University / Virtue AI LLM evaluation & benchmarks

Welfare, Improvability, and Variance: A Principal-Agent Approach to Optimal Benchmark Item Aggregation

Benchmark aggregation is modeled as a principal-agent game where welfare loss depends on item alignment, improvability, and variance; auditing OLMES reveals Pareto-inferior items under pro-worker welfare.

Andreas Haupt, Justin Hartenstein, Anka Reuel-Lamparth, Mykel J Kochenderfer and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Google DeepMind Stanford Computer Science Department, Sta Google Deepmind / Harvard U Maryland, College Park Robot manipulation

Masked Visual Actions for Unified World Modeling

Masked Visual Actions expresses robot and object motion as revealed pixel trajectories to unify forward dynamics, planning, and inverse modeling in video world models with minimal finetuning.

Hadi Alzayer, Wenlong Huang, Haonan Chen, Christopher Luey and 7 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 9 on Hugging Face · Code ★ 110

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NeurIPS 2026Shanghai Jiao Tong AMAP, Alibaba Group Nanyang Technological JD Explore Academy TTI Chicago Video generation

PermaVid: Consistent Video Generation Across Edits via Disentangled Context Memory

PermaVid disentangles video memory into RGB appearance and depth structure with edit-aware updates to maintain long-term consistency across modifications.

Shuai Yang, Bingjie Gao, Ziwei Liu, Jiaqi Wang and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 6 on Hugging Face · Code ★ 44

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NeurIPS 2026Stanford Human-AI interaction

Causal Effects with Unobserved Unit Types in Interacting Human–AI Systems

Using a human-AI prior and causal message passing framework, varying subpopulation composition and treatment exposure consistently identifies human-specific causal effects without observing unit types or interaction networks.

William Overman, Mohamad Sadegh Shirani Faradonbeh, Mohsen Bayati

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Department of Computer Science a Chinese University of Hong Kong Stanford The Chinese University of Hong K Genomics & single-cell

Towards Scalable Context-Aware Single-Cell Spatial Transcriptomics Prediction from Histology Images

CELLO predicts single-cell spatial transcriptomics from histology via grid sampling and distance-decay cross-attention, achieving 14x faster inference than DeepSpot2Cell without upstream segmentation.

Zijun Gao, Chunbin Gu, Xiangde Luo, Jinxi Xiang and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightKorea Advanced Institute of Scie KAIST KRAFTON U California, Los Angeles Stanford AutoML & architecture search

AMUSE: Anytime Muon with Stable Gradient Evaluation

AMUSE integrates Muon's rapid bulk progress with Schedule-Free averaging via time-varying interpolation to suppress oscillations, requiring no learning rate schedules and improving training efficiency across vision and LLM tasks.

Jueun Kim, Baekrok Shin, Jihun Yun, Beomhan Baek and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face

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NeurIPS 2026OralAnthropic MATS Stanford Google DeepMind AI oversight & deception

Neural Chameleons: Language Models Can Learn to Hide Their Thoughts from Unseen Activation Monitors

Fine-tuned LLMs learn to selectively hide internal representations from unseen activation monitors via low-dimensional subspace manipulation, evading even post-hoc safety probes with modest capability loss.

Max McGuinness, Alex Serrano Terre, Luke Bailey, Scott Emmons

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Stanford Vision-language-action models

APIVOT: Adaptive Planning with Interleaved Vision-Language Thoughts

APIVOT adaptively interleaves language and visual reasoning for robot planning, outperforming baselines on long-horizon kitchen tasks with greatest gains in spatially constrained settings.

Emily Jin, Joy Hsu, Yiqing Xu, Weiyu Liu and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026OralStanford Columbia Florida State Cold Spring Harbor Laboratory Computational neuroscience

BEAST3D: animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting

BEAST3D relates 3D behavioral features from multi-view video to neural activity via Gaussian splatting. It establishes a versatile framework for behavioral analysis using 3D structure in laboratory recordings.

Yanchen Wang, Lenny Aharon, Wangshu Zhu, Kyle Daruwalla and 6 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Mechanistic interpretability

Artificial Aphasias in Lesioned Language Models

Lesioning language models to mimic aphasia reveals distinct artificial symptom profiles across components and depths, indicating human aphasias depend heavily on learning and processing specifics.

Nathan Roll, Jill Kries, Laura Gwilliams, Cory Shain

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Cornell Stanford Cornell Tech Quantization

RaZeR: Pushing the Limits of NVFP4 Quantization with Redundant Zero Remapping

RaZeR remaps redundant NVFP4 zero values via block scaling bits to improve LLM quantization accuracy, reducing perplexity loss by up to 34.6%.

Yuzong Chen, Xilai Dai, Jake Hyun, Chi-Chih Chang and 5 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Peking Stanford Robot manipulation

JODA: Composable Joint Dynamics for Articulated Objects

JODA parameterizes articulated joint dynamics as structured three-channel fields via PCHIP interpolation, inferring and refining them from visual observations using vision-language models for controllable simulation.

Tianhong Gao, Cheng Yu, Yinghao Xu, Mengyu Chu

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Northwestern Stanford Probing & representation analysis

RAPTOR: Ridge-Adaptive Logistic Probes

RAPTOR is a ridge-regularized logistic probe that uses validation-tuned L2 penalties to extract accurate, stable concept vectors with low training cost for activation steering. It matches or exceeds baseline accuracy and stability across instruction-tuned LLMs, with theoretical analysis via CGMT exp

Ziqi Gao, Yaotian Zhu, Qingcheng Zeng, Xu Zhao and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 8 on Hugging Face

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NeurIPS 2026NVIDIA Stanford Long-context modeling

Gated DeltaNet-2: Decoupling Erase and Write in Linear Attention

Gated DeltaNet-2 decouples erase and write with channel-wise gates to improve linear attention, achieving top performance among recurrent and hybrid models at 1.3B scale with strong long-context retrieval.

Ali Hatamizadeh, Yejin Choi, Jan Kautz

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 30 on Hugging Face · Code ★ 326

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NeurIPS 2026Stanford Google DeepMind Instruction tuning

Subliminal Learning Is Steering Vector Distillation

Subliminal learning is steering vector distillation where students learn teachers' hidden traits via single steering vectors, requiring adaptive optimizers and failing across models.

Camila Blank, Agam Bhatia, Senthooran Rajamanoharan, Arthur Conmy and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Yale Stanford U Chicago U Chicago Booth School of Busine Toyota Technological Institute a LLM reasoning & chain of thought

INFUSER: Influence-Guided Self-Evolution Improves Reasoning

INFUSER co-evolves a question generator and solver via influence-guided rewards, improving reasoning by over 20% on math benchmarks without curated data.

Siyu Chen, Miao Lu, Beining Wu, Heejune Sheen and 6 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026U Minnesota Texas A&M Texas A&M University - Colle U Minnesota - Twin Cities Stanford 3D vision & reconstruction

DarkVGGT: Seeing Through Darkness Using Thermal Geometry without Daylight Tax

DarkVGGT uses physics-aware thermal modeling and geometry-shared routing to boost feed-forward 3D reconstruction in darkness without impairing daylight performance.

Minseong Kweon, Wenyuan Zhao, Nuo Chen, Lulin Liu and 5 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Stanford Retrieval-augmented generation

SLIDERS: Systematic Reviews via Automated Evidence Synthesis and Reconciliation

SLIDERS automates systematic reviews via LLM-based evidence extraction and reconciliation, achieving near 90% accuracy over multi-million-token corpora and answering 58-78% of follow-up questions correctly.

Harshit Joshi, Priyank Shethia, Jadelynn Dao, Monica Lam

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 16 on Hugging Face · Code ★ 31

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NeurIPS 2026Gatsby Computational Neuroscienc University College London, Unive IST Austria Stanford Deep learning theory

Optimal Representation Size: High-Dimensional Analysis of Pretraining and Linear Probing

High-dimensional analysis of pretraining via PCA and linear probing derives exact errors versus representation size, showing compression helps with abundant unlabeled but scarce labeled data.

Valentina Njaradi, Clémentine Dominé, Rachel A Swanson, Marco Mondelli and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford U Toronto EPFL - EPF Lausanne Stanford University / Virtue AI LLM evaluation & benchmarks

Efficient Prediction of Pass@k Scaling in Large Language Models

Standard pass@k scaling laws suffer statistical shortcomings, so a beta-binomial framework and dynamic sampling strategy more accurately predict rare LLM capabilities and risks from limited data.

Joshua Kazdan, Colin Sullivan, Rylan Schaeffer, Youssef Allouah and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Carnegie Mellon Stanford Learning theory

Intrinsic-dimension empirical Bernstein inequalities for bounded self-adjoint operators

Empirical Bernstein inequalities for bounded self-adjoint operators replace unknown variance with data-driven estimates and scale with intrinsic dimension for dimension-free, infinite-dimensional guarantees.

Diego Martinez Taboada, Aaditya Ramdas

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Stanford University / humans&amp RL for LLMs

Neural Garbage Collection: Learning to Forget while Learning to Reason

Neural Garbage Collection trains language models via reinforcement learning to evict KV cache entries during reasoning, achieving 2-3x compression with minimal accuracy loss.

Michael Li, Jubayer Ibn Hamid, Emily Fox, Noah Goodman

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 2 on Hugging Face

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NeurIPS 2026Stanford Stanford Deep RL