149 citations · 475 across the 69 of their papers we have counts for
70 papers
DynamicBench: Evaluating Real-Time Report Generation in Large Language Models
Jingyao Li, Hao Sun, Zile Qiao +5
Traditional benchmarks for large language models (LLMs) typically rely on static evaluations through storytelling or opinion expression, which fail to capture the dynamic requireme…
SynWorld: Virtual Scenario Synthesis for Agentic Action Knowledge Refinement
Runnan Fang, Xiaobin Wang, Yuan Liang +8
In the interaction between agents and their environments, agents expand their capabilities by planning and executing actions. However, LLM-based agents face substantial challenges…
Agentic Knowledgeable Self-awareness
Shuofei Qiao, Zhisong Qiu, Baochang Ren +8
Large Language Models (LLMs) have achieved considerable performance across various agentic planning tasks. However, traditional agent planning approaches adopt a "flood irrigation"…
EvolveSearch: An Iterative Self-Evolving Search Agent
Dingchu Zhang, Yida Zhao, Jialong Wu +8
The rapid advancement of large language models (LLMs) has transformed the landscape of agentic information seeking capabilities through the integration of tools such as search engi…
MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability
Weiqi Wu, Xin Guan, Shen Huang +6
Retrieval-Augmented Language Models (RALMs) represent a classic paradigm where models enhance generative capabilities using external knowledge retrieved via a specialized module. R…
ZeroSearch: Incentivize the Search Capability of LLMs without Searching
Hao Sun, Zile Qiao, Jiayan Guo +7
Effective information searching is essential for enhancing the reasoning and generation capabilities of large language models (LLMs). Recent research has explored using reinforceme…