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20232026
most citedThe Rise and Potential of Large Language Model Based Agents: A Survey

256 citations · 261 across the 24 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

NovGauge: A Fine-Grained Benchmark for Diagnosing LLMs' Capability in Paper Novelty Assessment

Guoqiang Zhang, Kexin Tan, Ming Zhang +12

Large language models (LLMs) are increasingly used in peer review at major AI conferences, yet novelty remains a persistent weak point. Existing benchmarks assess novelty as a sing…

cs.AI2026

JFTA-Bench: Evaluate LLM's Ability of Tracking and Analyzing Malfunctions Using Fault Trees

Yuhui Wang, Zhixiong Yang, Ming Zhang +10

In the maintenance of complex systems, fault trees are used to locate problems and provide targeted solutions. To enable fault trees stored as images to be directly processed by la…

cs.AI2024

TransferTOD: A Generalizable Chinese Multi-Domain Task-Oriented Dialogue System with Transfer Capabilities

Ming Zhang, Caishuang Huang, Yilong Wu +10

Task-oriented dialogue (TOD) systems aim to efficiently handle task-oriented conversations, including information collection. How to utilize TOD accurately, efficiently and effecti…

cs.AI2023

LLMEval: A Preliminary Study on How to Evaluate Large Language Models

Yue Zhang, Ming Zhang, Haipeng Yuan +5

Recently, the evaluation of Large Language Models has emerged as a popular area of research. The three crucial questions for LLM evaluation are ``what, where, and how to evaluate''…

cs.AI2023256 cited

The Rise and Potential of Large Language Model Based Agents: A Survey

Zhiheng Xi, Wenxiang Chen, Xin Guo +26

For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing the human level, with AI agents considered a promising vehicle for this pursuit. AI a…