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Towards Noise‐Robust Multi‐Agent Imitation Learning via Global Credit Sequence Decoding
Tianchen Zhu, Yue Qiu, Haoyi Zhou, Daqing Li
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Unified Neural Scaling Laws
Ethan Caballero, Priyank Jaini, David Krueger, Irina Rish
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
GaussGym: An open-source real-to-sim framework for learning locomotion from pixels
Alejandro Escontrela, Justin Kerr, Jonas Frey, Yan Duan, Carmelo Sferrazza, Pieter Abbeel
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Beyond Truthfulness: Evaluating Honesty in Large Language Models
Richard Ren, Arunim Agarwal, Mantas Mazeika, Cristina Menghini, Brad Kenstler, Robert Vacareanu, Mick Yang, Isabelle Barrass, Alice Gatti, Xuwang Yin, Eduardo Trevino, Matias Geralnik, Dean Lee, Summer Yue, Dan Hendrycks
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
TIDAL: A Temporal Causal Diffusion Framework for Visualizing Knee Osteoarthritis Treatment Outcomes
Anthony Cuturrufo, Fred Xu, Arvind Murari Vepa, David R. Bakal, Veena K. Ranganath, Yizhou Sun, Wei Wang
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Beyond Hard Supervised Fine-tuning: Enhancing Image-text Alignment of Strong Models with Weak Models
Jinhao Li, Sarah Monazam Erfani, Lei Feng, Guangrui Li, James Bailey, Feng Liu
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Less is More: Resource-Efficient Low-Rank Adaptation
Chunlin Tian, Xuyang Wei, Huanrong Liu, Yiming Luo, Zhijiang Guo, Li Li
- 20 Sept 2025 (modified: 29 Nov 2025)
- ICLR 2026 Conference Withdrawn Submission
- Readers: Everyone
Origins and roles of world representations in neural networks
Core Francisco Park
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Maximally Useful and Minimally Redundant: The Key to Self Supervised Learning for Imbalanced Data
Yash Kumar Sharma, Vineet Padmanabhan, Wilson Naik Bhukya
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Towards Generalizable Context-aware Anomaly Detection: A Large-scale Benchmark in Cloud Environments
Xinkai Zou, Xuan Jiang, Ruikai Huang, Haoze He, Parv kapoor, Hongrui Wu, Yibo Wang, Jian Sha, Xiongbo Shi, Zixun Huang, Jinhua Zhao
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Towards a Comprehensive Solution for Generating Synthetic Human Mobility Data from Limited Input Data
Ronald H Davies, Rajiv Ramnath
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Ada-Search: Balancing Parametric Knowledge and Search in Large Language Models via Reinforcement Learning
Tzu-Han Lin, Wei-Lin Chen, Chen-An Li, Hung-yi Lee, Yun-Nung Chen, Yu Meng
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Minimalist Explanation Generation and Circuit Discovery
Pirzada Suhail, Aditya Anand, Amit Sethi
- 20 Sept 2025 (modified: 23 Nov 2025)
- ICLR 2026 Conference Withdrawn Submission
- Readers: Everyone
DualFusion: Dual Adaptive Fusion for Multi-View Pedestrian Detection via View Reliability Modeling and Channel Reweighting
Weihang Kong, Yong Wang, He Li, Xingchen Zhang
- 20 Sept 2025 (modified: 14 Nov 2025)
- ICLR 2026 Conference Withdrawn Submission
- Readers: Everyone
TimeHC-RL: Temporal‑aware Hierarchical Cognitive Reinforcement Learning for Enhancing LLMs' Social Intelligence
Guiyang Hou, Gao Xing, Yuchuan Wu, Xiang Huang, Wenqi Zhang, Zhe Zheng, Yongliang Shen, Jialu Du, Fei Huang, Yongbin Li, Weiming Lu
- 20 Sept 2025 (modified: 04 Dec 2025)
- ICLR 2026 Conference Withdrawn Submission
- Readers: Everyone
What is Important? Internal Interpretability of Models Processing Data with Inherent Structure
Bartłomiej Wójcik, Arkadiusz Tomczyk
- 20 Sept 2025 (modified: 03 Dec 2025)
- ICLR 2026 Conference Withdrawn Submission
- Readers: Everyone
ALPS: Adaptive LLM Pruning via Gradient Search in Learned Representation Space
Chunlin Tian, Zhiyuan Ning, Xinpeng Qin, Yiming Luo, KaHou Tam, Yebo Wu, Yuanchun Zhou, Li Li
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Auto-Comp: An Automated Pipeline for Scalable Compositional Probing of Contrastive Vision-Language Models
Cristian Sbrolli, Matteo Matteucci, Toshihiko Yamasaki
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Training-free AI-generated Image Detection via Spectral Artifacts
Kangryun Moon, Sungik Choi, Hankook Lee
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Implicit Regularization of SGD Reduces Shortcut Learning
Nahal Mirzaie, Alireza Alipanah, Ali Abbasi, Amirmahdi Farzane, Hossein Jafarinia, Erfan Sobhaei, Mahdi Ghaznavi, Amir Najafi, Mahdieh Soleymani Baghshah, Mohammad Hossein Rohban
- Published: 26 Jan 2026, Last Modified: 11 Apr 2026
- ICLR 2026 Poster
- Readers: Everyone
Generative Traffic Simulations
Tanha Tasfia, Sercan Aygun
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Exploring Expert Failures Improves LLM Agent Tuning
Li-Cheng Lan, Andrew Bai, Minhao Cheng, Cho-Jui Hsieh, Tianyi Zhou
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Find tailored step example for next step: A Targeted Step-wise Retrieval Framework for Guiding LLM Reasoning
Cheng Yang, Zhenya Huang, Liyang He, Weibo Gao, Wei Huang, Tong Wei, Qi Liu
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
The Unreasonable Effectiveness of Scaling Agents for Computer Use
Gonzalo Gonzalez-Pumariega, Vincent Tu, Chih-Lun Lee, Jiachen Yang, Ang Li, Xin Eric Wang
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone
Spectral Decomposed Variational Inference: A Principled Framework for Posterior Covariance Modeling
Yuhang Xi, Yu-Feng Yu, Chuan-Xian Ren, Zhao-Rong Lai, Hu Zhu
- 20 Sept 2025 (modified: 11 Feb 2026)
- Submitted to ICLR 2026
- Readers: Everyone

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