8 citations · 11 across the 16 of their papers we have counts for
Showing 2026 · cs.AIShow all
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cs.AI2026
Parason: Revealing Subtask and Trial Parallelism in LLM Reasoning
Zhengyang Zhang, Zijian Zhang, Jiaxuan Gao +4
Scaling test-time reasoning has substantially improved the problem-solving ability of large language models (LLMs), but standard autoregressive decoding still executes long reasoni…
cs.AI2026
MAGE: Meta-Reinforcement Learning for Language Agents toward Strategic Exploration and Exploitation
Lu Yang, Zelai Xu, Minyang Xie +4
Large Language Model (LLM) agents have demonstrated remarkable proficiency in learned tasks, yet they often struggle to adapt to non-stationary environments with feedback. While In…
cs.AI2026
From Self-Evolving Synthetic Data to Verifiable-Reward RL: Post-Training Multi-turn Interactive Tool-Using Agents
Jiaxuan Gao, Jiaao Chen, Chuyi He +3
Interactive tool-using agents must solve real-world tasks via multi-turn interaction with both humans and external environments, requiring dialogue state tracking, multi-step tool…