11 papers
PAC: Progress-Augmented Advantage Curriculum for Multi-Task Reinforcement Learning of LLMs
Yuanqiang Yu, Yanzhao Zheng, Zhentao Zhang +8
Reinforcement learning (RL) is used to improve the reasoning abilities of LLMs, while training data span heterogeneous tasks. However, most RL post-training pipelines rely on fixed…
Rubrics to Tokens: Bridging Response-level Rubrics and Token-level Rewards in Instruction Following Tasks
Tianze Xu, Yanzhao Zheng, Pengrui Lu +11
Rubric-based Reinforcement Learning (RL) has emerged as a promising approach for aligning Large Language Models (LLMs) with complex, open-domain instruction following tasks. Howeve…
ContextBudget: Budget-Aware Context Management for Long-Horizon Search Agents
Yong Wu, YanZhao Zheng, TianZe Xu +9
LLM-based agents show strong potential for long-horizon reasoning, yet their context size is limited by deployment factors (e.g., memory, latency, and cost), yielding a constrained…
SkillRouter: Skill Routing for LLM Agents at Scale
YanZhao Zheng, ZhenTao Zhang, Chao Ma +8
Reusable skills let LLM agents package task-specific procedures, tool affordances, and execution guidance into modular building blocks. As skill ecosystems grow to tens of thousand…
AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts
Keyu Li, Junhao Shi, Yang Xiao +11
Large Language Models (LLMs) based autonomous agents demonstrate multifaceted capabilities to contribute substantially to economic production. However, existing benchmarks remain f…
Interaction as Intelligence Part II: Asynchronous Human-Agent Rollout for Long-Horizon Task Training
Dayuan Fu, Yunze Wu, Xiaojie Cai +13
Large Language Model (LLM) agents have recently shown strong potential in domains such as automated coding, deep research, and graphical user interface manipulation. However, train…
InnovatorBench: Evaluating Agents' Ability to Conduct Innovative LLM Research
Yunze Wu, Dayuan Fu, Weiye Si +13
AI agents could accelerate scientific discovery by automating hypothesis formation, experiment design, coding, execution, and analysis, yet existing benchmarks probe narrow skills…
A Self-Adaptive Frequency Domain Network for Continuous Intraoperative Hypotension Prediction
Xian Zeng, Tianze Xu, Kai Yang +4
Intraoperative hypotension (IOH) is strongly associated with postoperative complications, including postoperative delirium and increased mortality, making its early prediction cruc…
ResearcherBench: Evaluating Deep AI Research Systems on the Frontiers of Scientific Inquiry
Tianze Xu, Pengrui Lu, Lyumanshan Ye +2
The emergence of deep research systems presents significant capabilities in problem-solving, extending from basic queries to sophisticated research tasks. However, existing benchma…
Interaction as Intelligence: Deep Research With Human-AI Partnership
Lyumanshan Ye, Xiaojie Cai, Xinkai Wang +23
This paper introduces "Interaction as Intelligence" research series, presenting a reconceptualization of human-AI relationships in deep research tasks. Traditional approaches treat…
Mozart's Touch: A Lightweight Multi-modal Music Generation Framework Based on Pre-Trained Large Models
Jiajun Li, Tianze Xu, Xuesong Chen +2
In recent years, AI-Generated Content (AIGC) has witnessed rapid advancements, facilitating the creation of music, images, and other artistic forms across a wide range of industrie…