activity
20232025
most citedTool Learning with Large Language Models: A Survey

86 citations · 99 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2025

Efficient Thought Space Exploration Through Strategic Intervention

Ziheng Li, Hengyi Cai, Xiaochi Wei +4

While large language models (LLMs) demonstrate emerging reasoning capabilities, current inference-time expansion methods incur prohibitive computational costs by exhaustive samplin…

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

LLMs + Persona-Plug = Personalized LLMs

Jiongnan Liu, Yutao Zhu, Shuting Wang +6

Personalization plays a critical role in numerous language tasks and applications, since users with the same requirements may prefer diverse outputs based on their individual inter…

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.CL2023★ 3 cited

Towards Verifiable Text Generation with Evolving Memory and Self-Reflection

Hao Sun, Hengyi Cai, Bo Wang +5

Despite the remarkable ability of large language models (LLMs) in language comprehension and generation, they often suffer from producing factually incorrect information, also know…