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20232026
most citedTool Learning with Large Language Models: A Survey

86 citations · 99 across the 23 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

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The emergence of Retrieval-augmented generation (RAG) has alleviated the issues of outdated and hallucinatory content in the generation of large language models (LLMs), yet it stil…

cs.CL2024

Cross-model Control: Improving Multiple Large Language Models in One-time Training

Jiayi Wu, Hao Sun, Hengyi Cai +5

The number of large language models (LLMs) with varying parameter scales and vocabularies is increasing. While they deliver powerful performance, they also face a set of common opt…

cs.CL2024

AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning

Hao Sun, Jiayi Wu, Hengyi Cai +6

Recent advancements in large language models (LLMs) have been remarkable. Users face a choice between using cloud-based LLMs for generation quality and deploying local-based LLMs f…

cs.CL2024★ 1 cited

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…

cs.CL2024★ 86 cited

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…

cs.CL2024★ 8 cited

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…

cs.CL2024★ 1 cited

XLBench: A Benchmark for Extremely Long Context Understanding with Long-range Dependencies

Xuanfan Ni, Hengyi Cai, Xiaochi Wei +3

Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks but are constrained by their small context window sizes. Various efforts have been propos…

cs.CV2024

Text-Video Retrieval via Variational Multi-Modal Hypergraph Networks

Qian Li, Lixin Su, Jiashu Zhao +6

Text-video retrieval is a challenging task that aims to identify relevant videos given textual queries. Compared to conventional textual retrieval, the main obstacle for text-video…