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20222026
most citedA Comprehensive Study of Knowledge Editing for Large Language Models

21 citations · 51 across the 51 of their papers we have counts for

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7 papers · 1 filter

cs.IR2026

Think Thrice Before Reranking: Multi-perspective Evidence and Reasoning Integration for Text Reranking

Lijun Liu, Zhengzong Chen, Wenyan Li +2

Reasoning-based reranking with Large Language Models (LLMs) has shown promising improvements in text ranking. However, current methods predominantly rely on a single reasoning traj…

cs.IR2026

MagicSelector: Joint Optimization for Agent Tool Selection via Counterfactual Decomposition and Progressive Reranking

HONOR Agentic Search Team, Zhengzong Chen, Lei Tang +27

We present MagicSelector, a joint optimization framework integrating Counterfactual task decomposition, Progressive reranking, and Dynamic Top-K, designed to address the fundamenta…

cs.IR2026

PCTD: Preference-Guided Counterfactual Task Decomposition for Agent Tool Retrieval

Chu Zhao, Lei Tang, Minghang Li +5

Task decomposition aims to transform ambiguous instructions into executable atomic subtasks, thereby guiding high-precision tool retrieval. However, our analysis reveals that direc…

cs.IR2025

DecoupleSearch: Decouple Planning and Search via Hierarchical Reward Modeling

Hao Sun, Zile Qiao, Bo Wang +6

Retrieval-Augmented Generation (RAG) systems have emerged as a pivotal methodology for enhancing Large Language Models (LLMs) through the dynamic integration of external knowledge.…

cs.IR2025

WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent

Xinyu Geng, Peng Xia, Zhen Zhang +11

Web agents such as Deep Research have demonstrated superhuman cognitive abilities, capable of solving highly challenging information-seeking problems. However, most research remain…

cs.IR2025

Unsupervised Query Routing for Retrieval Augmented Generation

Feiteng Mu, Liwen Zhang, Yong Jiang +4

Query routing for retrieval-augmented generation aims to assign an input query to the most suitable search engine. Existing works rely heavily on supervised datasets that require e…

cs.IR2024

ProductAgent: Benchmarking Conversational Product Search Agent with Asking Clarification Questions

Jingheng Ye, Yong Jiang, Xiaobin Wang +5

This paper introduces the task of product demand clarification within an e-commercial scenario, where the user commences the conversation with ambiguous queries and the task-orient…