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Showing papers from CMU, Carnegie Mellon University Show all papers

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NeurIPS 2026Carnegie MellonCMU, Carnegie MellonRL for LLMs

Are we really tilting? The mechanics of reward guidance in flow and diffusion models

Sanjit Dandapanthula, Nicholas Boffi

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

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NeurIPS 2026Carnegie MellonCMU, Carnegie MellonSchool of Computer Science, CarnDeep RL

Implicit Goal Conditioning via Value Disaggregation

Shashwat Saxena, Mehul Goel, Sreyas Venkataraman, Sarvesh Patil and 1 more

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

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NeurIPS 2026CMU, Carnegie MellonCMU & MBZUAIGenomics & single-cell

Identifiable Feedback-Controlled Latent Flow for Unpaired Single-cell Spatio-Temporal Dynamics

Jianle Sun, Kun Zhang

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

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NeurIPS 2026Carnegie Mellon University, SeouCarnegie MellonSeoul NationalU FloridaEpic GamesVision-language models

MM-SCALE: Evaluating Evidence-Grounded Moral Judgment in Vision-Language Models

Eunkyu Park, Wesley Deng, Cheyon Jin, Matheus Kunzler Maldaner and 7 more

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

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NeurIPS 2026CMU, Carnegie MellonCarnegie MellonAmazonAdobeGoogle DeepMindMultimodal reasoning

ANCHOR: Audio-Visually Grounded Chain-of-Thought Reasoning Benchmark

Joel Julin, Souraja Kundu, Liza Dahiya, George Z Wei and 5 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 MellonCMU, Carnegie MellonCMUEfficient inference & serving

Learning Hierarchical Patch Splitting Policies for Faster Vision Transformers

Aditya Gupta, Jean S Dandurand, Kai Qiu, Rohan Choudhury and 1 more

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

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NeurIPS 2026U ChicagoCMU, Carnegie MellonChicago Booth School of BusinessCausal inference

ML-assisted Randomization Tests for A/B Experiments

Wenxuan Guo, JungHo Lee, Panos Toulis

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

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NeurIPS 2026Carnegie MellonU DelawareCMU, Carnegie MellonDeep learning theory

Beyond Eigenfunctions: Divergence Principal Functions for Representation Learning

Ritabrata Ray, Sahil Dharod, Burak Varıcı, Nicholas Boffi 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 2026PrincetonCMU, Carnegie MellonCarnegie MellonColfax InternationalNVIDIAEfficient attention & state-space models

GPU Hierarchy Meets Structured Matrices: Fast Algorithms for State-Space Models

Berlin Chen, Caitlin Wang, Aakash Sunil Lahoti, Kevin Li and 7 more

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

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NeurIPS 2026U WarsawUniwersytet Warszawski ul. KrakoCMU, Carnegie MellonMerck Healthcare KGaAHelmholtz Munich GmbHGenomics & single-cell

ImmuVis: Hyperconvolutional Foundation Models for Imaging Mass Cytometry

Dawid Uchal, Marcin Możejko, Krzysztof Gogolewski, Piotr Kupidura and 13 more

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

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NeurIPS 2026CMU, Carnegie MellonNational University of SingaporeCarnegie MellonDEVCOM Army Research LaboratoryGoogle Deepmind / HarvardNavigation & SLAM

Trajectory Planning without Trajectory Data: A Manifold-Guided Approach

Silong Yong, Anji Liu, Cunxi Dai, Carl Busart 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 2026Carnegie MellonRiceCMU, Carnegie MellonNational University of SingaporeSchool of Computer Science, CarnEfficient attention & state-space models

Vortex: Efficient and Programmable Sparse Attention Serving

Zhuoming Chen, Xinrui Zhong, Qilong Feng, Ranajoy Sadhukhan 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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57%Worth a look
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NeurIPS 2026CMU, Carnegie MellonIndian Institute of Technology DIndian Institute of Technology, Carnegie MellonMechanistic interpretability

The Unembedding Bottleneck: A Mechanistic Analysis of Single Digit Counting in LLMs

Satwik Sunnam, Raghav Magazine, Vatsalya Singh, Lavanya Kotha and 2 more

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

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NeurIPS 2026Carnegie MellonCMU, Carnegie MellonU WashingtonStanfordProteins

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 2026Carnegie MellonU Notre DameCMU, Carnegie MellonU PittsburghU North Carolina at Chapel HillLLM evaluation & benchmarks

Can Agents Price a Reaction? Evaluating LLMs on Chemical Cost Reasoning

Yuyang Wu, Yue Huang, Shuaike Shen, Xujian Wang and 7 more

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

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72%Highly rated
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NeurIPS 2026U TorontoHarvardMicrosoft Research New EnglandCMU, Carnegie MellonU LjubljanaDiffusion models

Test-time Scaling of Diffusions with Flow Maps

Flow Map Trajectory Tilting uses flow maps to enable principled diffusion test-time scaling with reward gradients, improving reward ascent and enabling complex image editing via vision-language models.

Amirmojtaba Sabour, Michael Albergo, Carles Domingo i Enrich, Nicholas Boffi and 3 more

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

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lenient 3/5
medium 5/10
strict 0/5
86%Must read
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NeurIPS 2026SpotlightCMU, Carnegie MellonDepartment of Computer Science, U WashingtonGoogleU North Carolina at Chapel HillPose & motion

MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction

MolmoMotion predicts goal-conditioned 3D point trajectories from visual history and language, outperforming baselines on PointMotionBench and improving robot manipulation and video synthesis.

Jianing Zhang, Chenhao Zheng, Yajun Yang, Rustin Soraki and 6 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 53 on Hugging Face · Code ★ 151

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 2/5
91%Must read
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NeurIPS 2026KAISTCarnegie MellonSchool of Computer Science, CarnKorea Advanced Institute of ScieCMU, Carnegie MellonLLM pretraining & scaling laws

Flow Map Language Models: One-step Language Modeling via Continuous Denoising

Continuous flow language models outperform discrete diffusion in quality and speed, and distilling their unique flow map enables one-step generation surpassing eight-step discrete diffusion.

Chanhyuk Lee, Jaehoon Yoo, Manan Agarwal, Sheel Shah and 5 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 4 on Hugging Face · Code ★ 172

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 2/5
72%Highly rated
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ICML 2026WorkshopCarnegie MellonCMU, Carnegie MellonSchool of Engineering and ApplieExplainable AI

Measuring Weak-to-Strong Legibility of Reasoning Models

This paper defines weak-to-strong legibility for reasoning models and argues existing efficiency metrics miss thoroughness needed for weak monitors.

Dani Roytburg, Shreya Sridhar, Daphne Ippolito

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

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lenient 5/5
medium 3/10
strict 0/5
91%Must read
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NeurIPS 2026Carnegie MellonCMU, Carnegie MellonSalesforce AI Research, UniversiSchool of Computer Science, CarnLLM evaluation & benchmarks

PACE: A Proxy for Agentic Capability Evaluation

PACE predicts agentic benchmark scores from small, selected non-agentic test subsets via regression, achieving under 4% error and over 0.80 correlation at under 1% evaluation cost.

Yueqi Song, Lintang Sutawika, Jiarui Liu, Lindia Tjuatja and 7 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 18 on Hugging Face

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AI panel: 18 of 20 reviewers recommend it
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medium 9/10
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