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20232026
most citedBeyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection

5 citations · 15 across the 21 of their papers we have counts for

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15 papers · 1 filter

cs.CL2026

WebSwarm: Recursive Multi-Agent Orchestration for Deep-and-Wide Web Search

Xiaoshuai Song, Liancheng Zhang, Kangzhi Zhao +8

Large language model (LLM)-based web search agents are transforming information seeking from simple factoid question answering into complex, deep-and-wide search and research-orien…

cs.CL2026

GISA: A Benchmark for General Information-Seeking Assistant

Yutao Zhu, Xingshuo Zhang, Maosen Zhang +9

The advancement of large language models (LLMs) has significantly accelerated the development of search agents capable of autonomously gathering information through multi-turn web…

cs.CL2026

EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis

Xiaoshuai Song, Haofei Chang, Guanting Dong +3

Large language models (LLMs) are expected to be trained to act as agents in various real-world environments, but this process relies on rich and varied tool-interaction sandboxes.…

cs.CL2025

ProgCo: Program Helps Self-Correction of Large Language Models

Xiaoshuai Song, Yanan Wu, Weixun Wang +3

Self-Correction aims to enable large language models (LLMs) to self-verify and self-refine their initial responses without external feedback. However, LLMs often fail to effectivel…

cs.CL2024

MTU-Bench: A Multi-granularity Tool-Use Benchmark for Large Language Models

Pei Wang, Yanan Wu, Zekun Wang +12

Large Language Models (LLMs) have displayed massive improvements in reasoning and decision-making skills and can hold natural conversations with users. Recently, many tool-use benc…

cs.CL2024★ 3 cited

Toward General Instruction-Following Alignment for Retrieval-Augmented Generation

Guanting Dong, Xiaoshuai Song, Yutao Zhu +3

Following natural instructions is crucial for the effective application of Retrieval-Augmented Generation (RAG) systems. Despite recent advancements in Large Language Models (LLMs)…