collaborators

7 papers

cs.AI2026

ScienceBuddy: Recursive-in-Recursive Self-Improvement for Interactive Scientific Agents

Shuhan Xue, Jianyuan Zhong, Ziyuan Nan +10

We introduce and release ScienceBuddy, an interactive scientific research workspace that brings continually improving scientific agents into researchers' everyday workflows. Scienc…

cs.AI2026

Recursive Experiential-Working Memory Evolution for Long-Horizon Agent Harnesses

Zhaochen Yu, Yingcheng Wu, Zhenfei Yin +5

Recursive self-improvement (RSI) remains hard in long-horizon tasks, where growing histories obscure the task state and misalign skill invocation. We introduce Recuris, a recursive…

cs.CL2026

Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning

Yinghui He, Ling Yang, Jiarui Liu +6

Long-horizon reasoning in recent LLMs demands that the model switch between distinct skills inside a reasoning chain, such as first doing a math derivation, then using the result t…

cs.CL2026

PAST-Bench: Benchmarking the Foundations of Recursive Self-Improvement in Personal Agents

Shuhan Xue, Zixin Ding, Yichen Shen +6

Recursive self-improvement requires agents to turn accumulated experience into better future behavior. Personal AI agents offer a concrete setting for studying this capability beca…

cs.AI2026

Science Earth: Towards A Planet-Scale Operating System for AI-Native Scientific Discovery

Zhe Zhao, Haibin Wen, Yingcheng Wu +10

Scientific discovery demands intelligence, perseverance, and serendipity across vast search spaces. Today, top scientific capabilities remain siloed--one AI system for biological a…

cs.CR2026

SeClaw: Spec-Driven Security Task Synthesis for Evaluating Autonomous Agents

Hao Cheng, Changtao Miao, Tianle Song +21

Autonomous LLM agents increasingly operate in stateful environments where they access tools, files, memory, and external services. While such capabilities enable complex real-world…

cs.AI2026

Autogenesis: A Self-Evolving Agent Protocol

Wentao Zhang, Zhe Zhao, Haibin Wen +4

LLM-based agent systems can adapt by revising prompts, constructing tools, and changing other runtime resources. Managing these heterogeneous updates requires a shared lifecycle fo…