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20232026
most citedDon't Make Your LLM an Evaluation Benchmark Cheater

18 citations · 59 across the 28 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

CoworkOS:Scaling Agent Coworkers for Real-world Automation

Jiajie Jin, Guanting Dong, Chengjun Pan +37

Rapid advances in cowork agents are shifting human-AI collaboration toward real-world automation, delivering software, designs, and other artifacts. However, such productivity work…

cs.AI2026

SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration

Yuyao Zhang, Junjie Gao, Zhengxian Wu +11

Recent advances in Tool-Integrated Large Language Models have made web search a core capability of information-seeking agents. However, as interaction histories grow, agents increa…

cs.AI2026★ 1 cited

OmniGAIA: Towards Native Omni-Modal AI Agents

Xiaoxi Li, Wenxiang Jiao, Jiarui Jin +10

Human intelligence naturally intertwines omni-modal perception -- spanning vision, audio, and language -- with complex reasoning and tool usage to interact with the world. However,…

cs.AI2025★ 1 cited

DeepAgent: A General Reasoning Agent with Scalable Toolsets

Xiaoxi Li, Wenxiang Jiao, Jiarui Jin +8

Large reasoning models have demonstrated strong problem-solving abilities, yet real-world tasks often require external tools and long-horizon interactions. Existing agent framework…

cs.AI2024

From Novice to Expert: LLM Agent Policy Optimization via Step-wise Reinforcement Learning

Zhirui Deng, Zhicheng Dou, Yutao Zhu +4

The outstanding capabilities of large language models (LLMs) render them a crucial component in various autonomous agent systems. While traditional methods depend on the inherent k…