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4 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Latest papers 22

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Immiscible Diffusion Policy: Preserving Multimodal Robot Actions through Label-Free Noise Assignment
Oct 7, 2026Xiao Zhang, Yuxin Chen, Zhixuan Liang +5Diffusion Policy Mode Collapse
University of California, Berkeley · Princeton University · The University of Texas at Austin
Visualizing Distribution Coverage in Generative Diffusion Models
Sep 30, 2026Yifei Wang, Xiaoyu Wu, Tsu-Jui Fu +4Diffusion Distillation Few-Step Diffusion Sampling
Rice University · Apple
Forty Shades of Blue: Quality-Diversity Alignment via Mode-Conditioned Reinforcement Learning
Sep 14, 2026Jiayi Yuan, Hangoo Kang, James Jihao Liu +4RL for Language Models Multi-Objective Language Model Alignment
University of Washington · 2Stanford University
Mode Coverage in Normalizing Flow Boltzmann Generators via Log-Ratio Variation
Sep 8, 2026Qi Feng, Rongjie Lai, Di Qi +1Normalizing Flows Molecular Generation
Department of Mathematics, Florida State University, Tallahassee, FL 32306 · Department of Mathematics, Purdue University, West Lafayette, IN 47907
Mask Forcing: Improving Autoregressive Video Diffusion Distillation via Dual-Noise Masking Rollout
Sep 8, 2026Zhuoran Zhao, Shengju Qian, Tongtong Liang +7Video Diffusion Models Diffusion Model Distillation
1HKUST(GZ) · 2HKUST · 3LIGHTSPEED +3
Beneath the Diff: Diagnosing and Mitigating Algorithmic Mode Collapse in Code-Level Autonomous Research Loops
Aug 31, 2026Bowei He, Weixu Zhang, Yili Jin +1Reward Hacking Automated Algorithm Discovery
MBZUAI · McGill University · MirrorSpace Technology +1
Optimizing Visual Generative Models via Distribution-wise Rewards
Jul 2, 2026Ruihang Li, Mengde Xu, Shuyang Gu +4Diffusion Model Fine-Tuning RL for Image Generation
University of Science and Technology of China · Shanghai Innovation Institute · Hunyuan Frontier Lab, Tencent +1
CreativityNeuro: Steering Language Model Weights to Improve Divergent Thinking and Reduce Mode Collapse
Jul 1, 2026Samuel Schapiro, Core Francisco Park, Felix Sosa +1Language Model Steering Computational Creativity
Univeristy of Illinois, Urbana-Champaign · Center for Brain Science, Harvard University · CBS-NTT Program in Physics of Intelligence, Harvard University +2
Pigeonholing: how bad prompts hurt models, causing collapse and mistakes
Jun 23, 2026Hyunji Nam, Keertana Chidambaram, Dorottya Demszky +1LLM Reliability In-Context Learning
Stanford University · University of Washington
Data-Forcing Distillation: Restoring Diversity and Fidelity in Few-Step Video Generation
Jun 16, 2026Siyi Chen, Shaowei Liu, Yixuan Jia +4Video Diffusion Models Diffusion Model Distillation
University of Michigan · NVIDIA · University of Illinois Urbana-Champaign
Beyond Imitation: Reflective On-Policy Self-Distillation for LLM Reasoning
May 27, 2026Ziqi Zhao, Xinyu Ma, Liu Yang +6On-Policy Self-Distillation Language Model Distillation
The Hong Kong Polytechnic University · Baidu Inc. · Shandong University +1
Mode-as-Sequence: Translating Multimodal Motion Prediction into Unified Sequential Mode Modeling
May 21, 2026Zikang Zhou, Haibo Hu, Xinhong Chen +5Probability Calibration Autonomous Driving
City University of Hong Kong · City University of Hong Kong (Dongguan) · Hon Hai Research Institute +1
Beyond Mode Collapse: Distribution Matching for Diverse Reasoning
May 19, 2026Xiaozhe Li, Yang Li, Xinyu Fang +10KL-Regularized RL RL for Language Model Reasoning
1Tongji University, China · 6Independent · 2Shanghai AI Laboratory, China +3
Driving Intents Amplify Planning-Oriented Reinforcement Learning
May 12, 2026Hengtong Lu, Victor Shea-Jay Huang, Chengmin Yang +4RL for Autonomous Driving Goal-Conditioned RL
Li Auto · Tsinghua University · CUHK MMLab
Unlocking LLM Creativity in Science through Analogical Reasoning
May 11, 2026Andrew Shen, Shaul Druckmann, James ZouAnalogical Reasoning Large Language Model-Guided Scientific Discovery
Stanford University
Self-Attention as a Covariance Readout: A Unified View of In-Context Learning and Repetition
May 11, 2026Haoren Xu, Guanhua FangSoftmax Attention Self-Attention
Fudan University
Annotations Mitigate Post-Training Mode Collapse
May 11, 2026Jacob Mitchell Springer, Madhu Advani, Lukas Aichberger +7Supervised Fine-Tuning Diverse Text Generation
Carnegie Mellon University · Apple · Johannes Kepler University Linz
TMPO: Trajectory Matching Policy Optimization for Diverse and Efficient Diffusion Alignment
May 9, 2026Jiaming Li, Chenyu Zhu, Nanxi Yi +9Diffusion Model Alignment Reward Hacking
1MAIR Lab, Huazhong University of Science and Technology · 2Kuaishou Technology · 3Nanyang Technological University +2
Escaping Mode Collapse in LLM Generation via Geometric Regulation
May 1, 2026Xin Du, Kumiko Tanaka-IshiiLanguage Model Steering Decoder-Only Language Models
Department of Communications and Computer Engineering, Waseda University, Tokyo, Japan · Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China · Department of Computer Science and Engineering, Waseda University, Tokyo, Japan
Pairing Regularization for Mitigating Many-to-One Collapse in GANs
Apr 22, 2026Kuan-Yu Lin, Yu-Chih Huang, Tie LiuGenerative Adversarial Networks Mode Collapse
Institute of Communications Engineering, National Yang Ming Chiao Tung University · Department of Electrical & Computer Engineering, Texas A&M University
Too Correct to Learn: Reinforcement Learning on Saturated Reasoning Data
Apr 20, 2026Zhenwen Liang, Yujun Zhou, Sidi Lu +3Reinforcement Learning RL for Language Model Reasoning
Tencent AI Lab · University of Notre Dame
Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)
Oct 27, 2025Liwei Jiang, Yuanjun Chai, Margaret Li +7Open-Ended Generation LLM Evaluation
University of Washington · Allen Institute for Artificial Intelligence · Carnegie Mellon University +3

Oct 7, 2026, cs.ROJ/K move · Enter open · S save

Immiscible Diffusion Policy: Preserving Multimodal Robot Actions through Label-Free Noise Assignment

Xiao Zhang, Yuxin Chen, Zhixuan Liang, Guojian Zhan+4

University of California, Berkeley · Princeton University · The University of Texas at Austin

Diffusion Policy Mode Collapse Robot Imitation Learning

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When diffusion policies were first introduced, they were expected to recover multi-modal action distributions. However, we find this expectation does not always hold, as diffusion policies often collapse to a single modality even when we guarantee the balance of dataset modalities and exact within-batch symmetry. Our analysis indicates that independent action-noise pairing contributes to this failure by increasing mixing and crossing among diffusion paths, which can produce averaged denoising responses and suppress modality-specific behavior. This issue is especially severe in robot planning, where action spaces are dense and low-dimensional, significantly increasing such mixing and crossing. To alleviate this problem, we propose Immiscible Diffusion Policy, a label-free training-time add-on to diffusion policy that uses action-noise assignment to preserve relatively distinct noise-to-action routes without modifying the policy architecture or inference procedure. Across five simulated and two real-world humanoid manipulation tasks spanning state, RGB, and point-cloud observations, our method significantly improves the policy's preservation of action modalities while maintaining strong task performance. It increases the proportion of the non-dominant modality by 6.0x-14.6x across three two-modality tasks and recovers demonstrated modalities that are entirely absent from vanilla policy rollouts on both four-modality tasks. These results demonstrate that Immiscible Diffusion Policy provides a simple yet robust approach to preserving action multi-modality in general robot learning tasks.

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