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Showing papers from CMU, Carnegie Mellon University Show all papers

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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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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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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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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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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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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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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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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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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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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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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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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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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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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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lenient 1/5
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57%Worth a look
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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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lenient 1/5
medium 0/10
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72%Highly rated
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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
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86%Must read
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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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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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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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AI panel: 8 of 20 reviewers recommend it
lenient 5/5
medium 3/10
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91%Must read
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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
lenient 5/5
medium 9/10
strict 4/5
86%Must read
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MonarchRT: Efficient Attention for Real-Time Video Generation

Monarch-RT factorizes video diffusion attention via Monarch matrices to reach 95% sparsity without quality loss, enabling 16 FPS real-time generation on one GPU with 1.4-11.8x kernel speedups.

Krish Agarwal, Zhuoming Chen, cheng Luo, Yongqi Chen 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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AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 2/5
83%Must read
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AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs

AstraFlow is a dataflow-oriented RL system for agentic LLMs that decouples rollout, dataflow, and training to enable multi-policy collaborative training with 2.7x faster training.

Haizhong Zheng, Yizhuo Di, Jiahui Wang, Shuowei Jin and 6 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 15 on Hugging Face · Code ★ 105

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 0/5
83%Must read
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Back to Blackwell: Closing the Loop on Intransitivity in Multi-Objective Preference Fine-Tuning

PROSPER defines the Maximum Entropy Blackwell Winner and applies it to multi-objective preference fine-tuning, outperforming baselines on instruction following and chat benchmarks.

Jiahao Zhang, Lujing Zhang, Keltin Grimes, Zhuohao Yu and 2 more

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

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AI panel: 13 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 1/5
72%Highly rated
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Concept Modulation Models: A Unified Framework for Identifiability and Extrapolation

Concept modulation models unify conditional latent variable model identifiability and extrapolation via attribute potentials and algebraic criteria for unseen attributes.

Soheun Yi, Yizhou Lu, Chandler Squires, Pradeep Ravikumar

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

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lenient 2/5
medium 5/10
strict 1/5
72%Highly rated
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Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences

Spatiotemporal Noise-Contrastive Estimation learns energy-based models via joint spatiotemporal differences to avoid failure modes of spatial or temporal methods alone, matching state-of-the-art density estimation.

Hanlin Yu, RuiKang OuYang, Partha Kaushik, Arto Klami 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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lenient 3/5
medium 5/10
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86%Must read
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Few-Step Cofolding with All-Atom Flow Maps

DeCAF distills all-atom biomolecular cofolding diffusion models into few-step flow maps with SE(3)-aligned endpoint losses, improving accuracy and physical validity at strict inference budgets.

Gianluca Scarpellini, Ron Shprints, Peter Holderrieth, Juno Nam 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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AI panel: 14 of 20 reviewers recommend it
lenient 3/5
medium 10/10
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91%Must read
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FineVLA: Fine-Grained Instruction Alignment for Steerable Vision-Language-Action Policies

FineVLA introduces fine-grained action-aligned supervision for steerable vision-language-action policies, yielding up to 86.8% simulation and 62.7 real-world success and boosting steerable control over coarse instructions.

Xintong Hu, Xuhong Huang, JINYU ZHANG, Yutong Yao and 8 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 9 on Hugging Face

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AI panel: 18 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 3/5
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Evaluating Test-Time Scaling of General LLM Agents

Realistic benchmark reveals LLM agents suffer scaling plateaus and verification gaps that prevent meaningful test-time compute gains.

Xiaochuan Li, Tianshi Ming, Pranav Setlur, Abhijay S Paladugu and 5 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 10 on Hugging Face · Code ★ 25

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 1/5
86%Must read
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Offline Reinforcement Learning for Plasma Control in Nuclear Fusion: Codebase and Benchmark

RL4F introduces an offline RL benchmark for tokamak plasma control using DIII-D dynamics, finding model-based methods perform best but no method dominates all tasks.

YANG FU, Haomin Bao, Rohit Sonker, Xiaoyan Hu 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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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 2/5
92%Must read
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OdysSim: Building Foundation Models for Human Behavior Simulation

OdysSim trains 8B behavioral foundation models via SOUL taxonomy and multi-stage recipes, ranking first on eight human simulation benchmarks while nearly matching real-user reaction alignment.

Xuhui Zhou, Weiwei Sun, Weihua Du, Jiarui Liu and 5 more

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

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AI panel: 19 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 4/5
76%Highly rated
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Few-Step Boltzmann Generators via Scalable Likelihood Flow Maps

SCALLOP introduces a Hutchinson-free likelihood distillation objective for few-step Boltzmann generators, reducing training variance and time while achieving up to 10x inference speedup.

RuiKang OuYang, Hanlin Yu, Xinyue Ai, Yutong He and 6 more

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

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AI panel: 10 of 20 reviewers recommend it
lenient 3/5
medium 7/10
strict 0/5
86%Must read
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Point4D: Long-range 4D Motion Reconstruction

Point4D infers dense 3D point trajectories across multi-hundred-frame videos via a decoupled query-based motion decoder, outperforming prior short-window feed-forward 4D methods.

Minsik Jeon, Jay Karhade, Deva Ramanan, Shubham Tulsiani

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

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AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 1/5
91%Must read
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Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation

MoLF dynamically routes optimizer updates between full fine-tuning and LoRA to match or beat the stronger static method across tasks, and its efficient variant surpasses AdaLoRA and AdaMix by up to 11.70 points.

Haozhan Tang, Xiuqi Zhu, Xinyin Zhang, Boxun Li and 2 more

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

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AI panel: 18 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 3/5