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20232026
most citedThe Rise and Potential of Large Language Model Based Agents: A Survey

256 citations · 279 across the 26 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

Entropy Is Not Enough: Unlocking Effective Reinforcement Learning for Visual Reasoning via Vision-Anchored Token Selection

Senjie Jin, Peixin Wang, Boyang Liu +8

While token-level entropy is commonly recognized as effective for credit assignment in text-only reinforcement learning with verifiable rewards (RLVR), it remains unclear whether t…

cs.AI2026

LifeAgentBench: Benchmarking LLMs for Long-Horizon, Cross-Dimensional Lifestyle Health Reasoning

Ye Tian, Zihao Wang, Onat Gungor +2

Personalized lifestyle health analysis requires long-horizon, multi-dimensional reasoning over heterogeneous lifestyle signals, and recent advances in mobile sensing and large lang…

cs.AI2024★ 2 cited

Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning

Zhiheng Xi, Wenxiang Chen, Boyang Hong +18

In this paper, we propose R: Learning Reasoning through Reverse Curriculum Reinforcement Learning (RL), a novel method that employs only outcome supervision to achieve the bene…

cs.AI2024★ 8 cited

Secrets of RLHF in Large Language Models Part II: Reward Modeling

Binghai Wang, Rui Zheng, Lu Chen +24

Reinforcement Learning from Human Feedback (RLHF) has become a crucial technology for aligning language models with human values and intentions, enabling models to produce more hel…

cs.AI2023★ 256 cited

The Rise and Potential of Large Language Model Based Agents: A Survey

Zhiheng Xi, Wenxiang Chen, Xin Guo +26

For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing the human level, with AI agents considered a promising vehicle for this pursuit. AI a…