86 citations · 301 across the 30 of their papers we have counts for
4 papers · 1 filter
Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents
Haoyu Wang, Sunhao Dai, Haiyuan Zhao +6
Previous studies have found that PLM-based retrieval models exhibit a preference for LLM-generated content, assigning higher relevance scores to these documents even when their sem…
From Exploration to Mastery: Enabling LLMs to Master Tools via Self-Driven Interactions
Changle Qu, Sunhao Dai, Xiaochi Wei +5
Tool learning enables Large Language Models (LLMs) to interact with external environments by invoking tools, serving as an effective strategy to mitigate the limitations inherent i…
Tool Learning with Large Language Models: A Survey
Changle Qu, Sunhao Dai, Xiaochi Wei +5
Recently, tool learning with large language models (LLMs) has emerged as a promising paradigm for augmenting the capabilities of LLMs to tackle highly complex problems. Despite gro…
Towards Completeness-Oriented Tool Retrieval for Large Language Models
Changle Qu, Sunhao Dai, Xiaochi Wei +5
Recently, integrating external tools with Large Language Models (LLMs) has gained significant attention as an effective strategy to mitigate the limitations inherent in their pre-t…