1 citations · 1 across the 12 of their papers we have counts for
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Agent Harness Distillation: Inference-Time Harness Extraction and Exploitation in Autonomous Multi-Agent Systems
Yu Cui, Wuli Yang, Yirui Shi +4
Autonomous multi-agent systems (AMAS) built on large language models (LLMs), such as Hermes, increasingly rely on inference-time harnesses to coordinate reasoning and action. Const…
Bidirectional Context Self-Distillation for Reinforcement Learning of Skill-Based LLM Agents
Tianjun Pan, Yuan Li, Hongda Wang +8
External natural-language skills provide large language model (LLM) agents with reusable and editable guidance for solving complex tasks. Yet their effectiveness depends not only o…
Segment-Aligned Policy Optimization for Multi-Modal Reasoning
Lei Gao, Zhuoming Li, Mengxi Jia +4
Existing reinforcement learning approaches for Large Language Models typically perform policy optimization at the granularity of individual tokens or entire response sequences. How…
Infrastructure for Valuable, Tradable, and Verifiable Agent Memory
Mengyuan Li, Lei Gao, Haoxuan Xu +5
Every API token you spend is your accumulated wealth; once you can prove its value and the effort behind it, you can resell it. As autonomous agents repeatedly call models and tool…