Reinforcement learning

Policy optimisation, reward modelling and RLHF — how models are trained by feedback rather than by labels.

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arXiv AI

Sep 30

Generative Support Realignment for Cross-Domain Offline Reinforcement Learning

arXiv:2605.13054v2 Announce Type: replace-cross Abstract: Cross-domain offline reinforcement learning learns a target policy from pre-collected source and target datasets with different dynamics. Whe...

By Minung Kim, Jeongmo Kim, Gwanwoo Choi, Seungyul Han

reinforcement-learning benchmarks

arXiv AI

Sep 30

AdvantageFlow: Regularized Advantage-Weighted RL in Flow Models

arXiv:2605.26013v2 Announce Type: replace-cross Abstract: We present AdvantageFlow, a forward-process reinforcement learning (RL) algorithm for rectified flow models. The algorithm minimizes an advan...

By Branislav Kveton, Anup Rao, Subhojyoti Mukherjee, Krishna Kumar Singh, Viet Dac Lai

diffusion reinforcement-learning

arXiv AI

Sep 30

F4R: Failure-Driven Recognition, Reconstruction, Refinement, and Redeployment for Continual Robot Self-Improvement

arXiv:2609.35575v2 Announce Type: replace-cross Abstract: The real-world performance of current vision-language-action models is fundamentally constrained by the limited coverage of expert demonstrat...

By Zhuoyuan Yu, Jiacheng Wang, Tianle Liu, Yihua Ren, Peng Yu, Chen Bai, Ziheng Zhang, Yufei Jia, Jindou Jia, Yuhang Zhang, Xinrui Zhang, Shang Yujing, Yuxiang Chen, Chuhao Zhou, Tiancai Wang, Jianfei Yang

agents reinforcement-learning robotics multimodal

arXiv Machine Learning

Sep 30

Fair Policy Optimization in Major-Minor Weakly Coupled Markov Decision Processes

arXiv:2609.36174v1 Announce Type: new Abstract: We consider fair resource allocation in sequential decision-making environments modeled as major-minor weakly coupled Markov decision processes (M2WCMD...

By Xiaohui Tu, Yossiri Adulyasak, Erick Delage

reinforcement-learning safety

arXiv Machine Learning

Sep 30

The Teacher Is a Direction, Not a Destination: Extrapolating RL-Induced Representation Residuals in On-Policy Distillation

arXiv:2609.36484v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student to match the teacher's next-token distributions on the student's own trajectories and has yielded substan...

By Hao Li, MeiJia Chen, Weijie Ren, Donghan Li, Zijun Tian, Jingchun Huang, Naibo Wang

reinforcement-learning efficiency

arXiv Machine Learning

Sep 30

Learned Reporting Preferences in RLVR Can Conflict with the Current Request

arXiv:2609.36587v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a prominent approach for improving language-model performance on reasoning tasks using...

By Yupeng Chang, Wenxuan Zhang, Yuan Wu

reinforcement-learning

arXiv Machine Learning

Sep 30

Looped Actor: Depth-Recurrent Reasoning Models for Reinforcement Learning

arXiv:2609.37432v1 Announce Type: new Abstract: Looped reasoning models repeatedly apply a shared set of parameters, enabling more computation without increasing the model size. These models also sup...

By T. Konstantin Rusch, Tim Seyde, Jared Boyer, Zach J. Patterson, Daniela Rus

llms agents reinforcement-learning robotics

arXiv Machine Learning

Sep 30

Explore Broadly, Reason Sharply: Push Small Models toward the Frontier via Sampling

arXiv:2609.38104v1 Announce Type: new Abstract: Power-sharpened sampling is an inference-time alternative to reinforcement-learning (RL) post-training for enhancing reasoning in large language models...

By Panagiotis Theodoropoulos, Nan Jiang, Xintong Duan, Ali Hasan, Yuriy Nevmyvaka, Evangelos A. Theodorou, Wei Deng

llms reinforcement-learning safety

arXiv Machine Learning

Sep 30

FastGuide: Accelerating Reward Guidance for Diffusion Large Language Models

arXiv:2609.36202v1 Announce Type: cross Abstract: Gradient-based reward guidance provides a flexible way to use downstream reward models to control masked diffusion language models at inference time....

By Darshan Thaker, Lachlan Ewen MacDonald, Ren\'e Vidal

llms diffusion reinforcement-learning benchmarks

arXiv Machine Learning

Sep 30

Finite-Sample Theory for Fitted Q-Iteration When Actions Are Functions

arXiv:2609.36390v1 Announce Type: cross Abstract: Offline reinforcement learning seeks optimal decision rules from previously collected data. In some applications, a decision can be an entire functio...

By Gefei Lin, Rui Miao, Xiaoke Zhang

reinforcement-learning robotics

arXiv Machine Learning

Sep 30

PoE-Fuse: Precision-Weighted Expert Fusion for Bi-Temporal Change Understanding

arXiv:2609.37485v1 Announce Type: cross Abstract: Bi-temporal change understanding, which localizes and characterizes what changed between two satellite images, is central to disaster response and en...

By Haruki Watase, Shunya Nagashima, Takayuki Nishimura

llms reinforcement-learning fine-tuning multimodal

arXiv Machine Learning

Sep 30

Fooling Algorithms in Non-Stationary Bandits using Belief Inertia

arXiv:2511.05620v2 Announce Type: replace Abstract: We study worst-case dynamic regret of specific multi-armed bandit algorithms on piecewise-stationary instances with at most one breakpoint. Our con...

By Gal Mendelson, Eyal Tadmor

reinforcement-learning

arXiv Machine Learning

Sep 30

IR-SIM: A Lightweight Declarative Simulator for Navigation Learning and Benchmarking

arXiv:2606.08729v2 Announce Type: replace-cross Abstract: Developing navigation policies requires simulation scenarios that support repeatable training and evaluation. Despite the availability of num...

By Ruihua Han, Shuai Wang, Chengyang Li, Rui Gao, Xinyi Wang, Zhe Liu, Guoliang Li, Yupu Lu, Qi Hao, Jia Pan, Hengshuang Zhao

llms agents reinforcement-learning robotics benchmarks

arXiv AI

Sep 30

Diffusion Policy Improvement with Proposal-Conditioned Refinement Flows

arXiv:2609.36812v1 Announce Type: cross Abstract: Diffusion and flow policies can model complex behaviors in offline reinforcement learning (RL). However, penalizing their KL divergence from the beha...

By Junhyun Ha, Juho Lee, Byungwoo Park

diffusion reinforcement-learning fine-tuning

arXiv Machine Learning

Sep 30

OpenTumorBoard: A Real-World Benchmark of Multidisciplinary Tumor Board Discussion Trajectories

arXiv:2609.32810v2 Announce Type: replace-cross Abstract: Multidisciplinary tumor boards integrate multimodal clinical observations and longitudinal patient histories through specialist discussions,...

By Anqi Li, Zhixuan Ge, Yixuan Duan, Jiarong Qian, Chi-Yu Chen, MingYu Lu, Huan-Yu Hsu, Yu Gu, Yue Guo, Sheng Wang, Wei Qiu, Hanwen Xu

llms reinforcement-learning fine-tuning multimodal benchmarks safety

arXiv Computation and Language

Sep 30

Can Language Models Learn to Forecast Stock Prices

arXiv:2609.36914v1 Announce Type: new Abstract: Post-training has been shown to significantly improve language models' performance on tasks with verifiable outcomes, including mathematical reasoning,...

By Jiacheng Guo, Suozhi Huang, Shuzhen Li, Yunlong Gao, Zerui Cheng, Jason Ge, Shushu Liang, Zihao Li, Hao Lu, Ming Yin, Shilong Liu, Jiashuo Liu, Xu Kuang, Mengdi Wang

llms agents reinforcement-learning fine-tuning benchmarks

arXiv Computation and Language

Sep 30

SemOPT: Fixing Semantic Errors in LLM-based Optimization Modeling via Reward-Guided Search

arXiv:2609.37361v1 Announce Type: new Abstract: Operations research supports decision-making in domains such as energy, economics, and healthcare. Solving operations research problems typically begin...

By Zetong Zhou, Wentao Zhang, Jingyuan Wang, Yifan Yang, Zizhuo Wang, Shixi Hu

llms reinforcement-learning benchmarks

arXiv Computation and Language

Sep 30

POET: Preference Optimization for Enhanced Text-to-Image Generation

arXiv:2510.12041v3 Announce Type: replace Abstract: Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models often struggle with simple or underspecifie...

By Ruibo Chen, Jiacheng Pan, Heng Huang, Zhenheng Yang

llms diffusion reinforcement-learning fine-tuning multimodal benchmarks safety

arXiv Computation and Language

Sep 30

HPRO: Hierarchical Progressive Reward Optimization via Preference Extraction for Emotional Text-to-Speech

arXiv:2606.28249v2 Announce Type: replace-cross Abstract: Recently, Large Language Model (LLM)-based Text-to-Speech (TTS) models have achieved remarkable naturalness. However, the standard Supervised...

By Sihang Nie, Xiaofen Xing, Rui Xing, Haoming Li, Ruitong Xiao, Jingyuan Xing, Baiji Liu, Xiangmin Xu

llms diffusion reinforcement-learning fine-tuning multimodal

arXiv Computer Vision

Sep 30

Xiaomi-OCR-0 Technical Report

arXiv:2609.36136v1 Announce Type: new Abstract: Compact OCR-specific vision-language models achieve strong document parsing performance, but often rely on costly supervision and focus primarily on vi...

By Xin Chen, Anan Du, Feng Feng, Pei Fu, Jian Luan, Longwei Xu, Shaojie Zhang, Hang Li, Heng Qu, Cheng Tan

llms computer-vision reinforcement-learning multimodal benchmarks

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