10 papers · 1 filter
SEAL: Can Saturated Benchmarks Be Revived by LLM-as-a-Meta-Judge?
Jiamin Chen, Yidi Wu, Qiexiang Wang +6
Widely used language-model benchmarks are increasingly saturated, with frontier systems often receiving near-tied scores that standard metrics cannot resolve. Rather than construct…
DirectorBench: Diagnosing Long-Form Video Generation with Personalized Multi-Agent Evaluation
Jiamin Chen, Qianben Chen, Jiawen Zhang +5
Long-form video generation is rapidly moving from short, single-scene synthesis toward minute-long, multi-shot creation with narrative structure, cinematic control, audio, and cros…
GenesisFunc: Multi-Agent Data Generation for Accurate and Generalizable Function-Calling
Hao-Xiang Xu, Chong Deng, Jiaqing Liu +5
Large Language Models (LLMs) extend their capabilities through function-calling (FC), which relies on training data with high quality, diversity, and broad coverage of scenario. Ho…
Search More, Think Less: Rethinking Long-Horizon Agentic Search for Efficiency and Generalization
Qianben Chen, Tianrui Qin, King Zhu +21
Recent deep research agents primarily improve performance by scaling reasoning depth, but this leads to high inference cost and latency in search-intensive scenarios. Moreover, gen…
O-Researcher: An Open Ended Deep Research Model via Multi-Agent Distillation and Agentic RL
Yi Yao, He Zhu, Piaohong Wang +12
The performance gap between closed-source and open-source large language models (LLMs) is largely attributed to disparities in access to high-quality training data. To bridge this…
How Far Are We from Genuinely Useful Deep Research Agents?
Dingling Zhang, He Zhu, Jincheng Ren +15
Deep Research Agents (DRAs) aim to automatically produce analyst-level reports through iterative information retrieval and synthesis. However, most existing DRAs were validated on…
O-Mem: Omni Memory System for Personalized, Long Horizon, Self-Evolving Agents
Piaohong Wang, Motong Tian, Jiaxian Li +8
Recent advancements in LLM-powered agents have demonstrated significant potential in generating human-like responses; however, they continue to face challenges in maintaining long-…
AFM: An Adaptive Agent Foundation Model for Tool-Aware Hybrid Reasoning
Qianben Chen, Jingyi Cao, Jiayu Zhang +12
Large language models split into two families: reasoning-centric LLMs, which strengthen internal chain-of-thought reasoning but cannot invoke external tools, and agentic LLMs, whic…
ACADREASON: Exploring the Limits of Reasoning Models with Academic Research Problems
Xin Gui, King Zhu, JinCheng Ren +17
In recent years, the research focus of large language models (LLMs) and agents has shifted increasingly from demonstrating novel capabilities to complex reasoning and tackling chal…
TaskCraft: Automated Generation of Agentic Tasks
Dingfeng Shi, Jingyi Cao, Qianben Chen +14
Agentic tasks, which require multi-step problem solving with autonomy, tool use, and adaptive reasoning, are becoming increasingly central to the advancement of NLP and AI. However…