7 papers
A Unified Algorithmic Framework for Hybrid Reinforcement Learning in Tabular MDPs with Shifted Transition Dynamics
Zheshun Wu, Renjie Zheng, Jinhang Zuo +2
This paper investigates a hybrid reinforcement learning setting in tabular Markov Decision Processes (MDPs), where an agent aims to learn an optimal policy by combining online inte…
Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents
Jiawei Huang, Qingping Yang, Renjie Zheng +1
Despite recent progress in Large Language Model (LLM) Agents for Software Engineering (SWE) tasks, end-to-end fine-tuning typically relies on verifiable terminal rewards such as wh…
UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
Haoming Wang, Haoyang Zou, Huatong Song +109
The development of autonomous agents for graphical user interfaces (GUIs) presents major challenges in artificial intelligence. While recent advances in native agent models have sh…
SciDA: Scientific Dynamic Assessor of LLMs
Junting Zhou, Tingjia Miao, Yiyan Liao +15
Advancement in Large Language Models (LLMs) reasoning capabilities enables them to solve scientific problems with enhanced efficacy. Thereby, a high-quality benchmark for comprehen…
Flaming-hot Initiation with Regular Execution Sampling for Large Language Models
Weizhe Chen, Zhicheng Zhang, Guanlin Liu +6
Since the release of ChatGPT, large language models (LLMs) have demonstrated remarkable capabilities across various domains. A key challenge in developing these general capabilitie…
Enhancing Multi-Step Reasoning Abilities of Language Models through Direct Q-Function Optimization
Kaixuan Ji, Guanlin Liu, Ning Dai +6
Reinforcement Learning (RL) plays a crucial role in aligning large language models (LLMs) with human preferences and improving their ability to perform complex tasks. However, curr…