activity
20232026
most citedChain of Agents: Large Language Models Collaborating on Long-Context Tasks

9 citations · 13 across the 18 of their papers we have counts for

collaborators
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7 papers · 1 filter

cs.AI2026

Harness^2: Recursive Agent Harnessing for an Open World

Ruiyao Xu, Yanfei Chen, Zhongying CuiZhu +6

LLM agents' capabilities depend not only on their underlying models but also on their execution harnesses. Recursive self-improvement (RSI) offers a promising approach to automatic…

cs.AI2026

EnvHarness: Awakening Static Worlds for Agent Learning

Chengsong Huang, Zifeng Wang, Rujun Han +14

LLM agents learn by interacting with environments, yet these environments are hand-built and static: blind to an agent's weaknesses, and quickly left behind as it improves. While r…

cs.AI2026

SkillOS: Learning Skill Curation for Self-Evolving Agents

Siru Ouyang, Jun Yan, Yanfei Chen +13

LLM-based agents are increasingly deployed to handle streaming tasks, yet they often remain one-off problem solvers that fail to learn from past interactions. Reusable skills disti…

cs.AI2026

SAGE: Steerable Agentic Data Generation for Deep Search with Execution Feedback

Fangyuan Xu, Rujun Han, Yanfei Chen +7

Deep search agents, which aim to answer complex questions requiring reasoning across multiple documents, can significantly speed up the information-seeking process. Collecting huma…

cs.AI2025★ 1 cited

Budget-Aware Tool Use Enables Effective Agent Scaling

Tengxiao Liu, Zifeng Wang, Jin Miao +12

Scaling test-time computation has been extended from language model reasoning to tool-augmented agents, where scaling involves not only thinking in tokens but also acting via tool…

cs.AI2025

ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory

Siru Ouyang, Jun Yan, I-Hung Hsu +14

With the growing adoption of large language model agents in persistent real-world roles, they naturally encounter continuous streams of tasks. A key limitation, however, is their f…

cs.AI2025★ 1 cited

PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving

Mihir Parmar, Xin Liu, Palash Goyal +11

Recent agent frameworks and inference-time algorithms often struggle with complex planning problems due to limitations in verifying generated plans or reasoning and varying complex…