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20242026
most citedMAS-KCL: Knowledge component graph structure learning with large language model-based agentic workflow

5 citations · 5 across the 13 of their papers we have counts for

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8 papers · 1 filter

cs.CL2026

Retrieval, Reward, and Training Protocols: What Matters in Training Search Agents?

Yibo Zhao, Zichen Ding, Jiayi Wu +2

Search agents powered by large language models can autonomously decompose queries, retrieve information, and synthesize answers through multi-step reasoning. However, the rapid gro…

cs.CL2026

Negative Advantages Is a Double-Edged Sword: Calibrating advantages in GRPO for Search Agents

Jiayi Wu, Ruobing Xie, Zeqian Huang +6

Search agents achieve strong question-answering performance through multi-turn interactions with search engines, with Group Relative Policy Optimization (GRPO) being a widely used…

cs.CL2025

Reasoning About the Unsaid: Misinformation Detection with Omission-Aware Graph Inference

Zhengjia Wang, Danding Wang, Qiang Sheng +2

This paper investigates the detection of misinformation, which deceives readers by explicitly fabricating misleading content or implicitly omitting important information necessary…

cs.CL2025

ImCoref-CeS: An Improved Lightweight Pipeline for Coreference Resolution with LLM-based Checker-Splitter Refinement

Kangyang Luo, Yuzhuo Bai, Shuzheng Si +9

Coreference Resolution (CR) is a critical task in Natural Language Processing (NLP). Current research faces a key dilemma: whether to further explore the potential of supervised ne…

cs.CL2025

Towards AI Search Paradigm

Yuchen Li, Hengyi Cai, Rui Kong +20

In this paper, we introduce the AI Search Paradigm, a comprehensive blueprint for next-generation search systems capable of emulating human information processing and decision-maki…

cs.CL2024

PA-RAG: RAG Alignment via Multi-Perspective Preference Optimization

Jiayi Wu, Hengyi Cai, Lingyong Yan +5

The emergence of Retrieval-augmented generation (RAG) has alleviated the issues of outdated and hallucinatory content in the generation of large language models (LLMs), yet it stil…