activity
20232026
most citedTPE: Towards Better Compositional Reasoning over Conceptual Tools with Multi-persona Collaboration

3 citations · 8 across the 17 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CL2024

UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models

Boyang Xue, Fei Mi, Qi Zhu +6

Despite demonstrating impressive capabilities, Large Language Models (LLMs) still often struggle to accurately express the factual knowledge they possess, especially in cases where…

cs.CL2024

MlingConf: A Comprehensive Study of Multilingual Confidence Estimation on Large Language Models

Boyang Xue, Hongru Wang, Rui Wang +5

The tendency of Large Language Models (LLMs) to generate hallucinations raises concerns regarding their reliability. Therefore, confidence estimations indicating the extent of trus…

cs.SE2024

AppBench: Planning of Multiple APIs from Various APPs for Complex User Instruction

Hongru Wang, Rui Wang, Boyang Xue +5

Large Language Models (LLMs) can interact with the real world by connecting with versatile external APIs, resulting in better problem-solving and task automation capabilities. Prev…

cs.CL2024★ 1 cited

Role Prompting Guided Domain Adaptation with General Capability Preserve for Large Language Models

Rui Wang, Fei Mi, Yi Chen +5

The growing interest in Large Language Models (LLMs) for specialized applications has revealed a significant challenge: when tailored to specific domains, LLMs tend to experience c…

cs.CL2024★ 1 cited

UniRetriever: Multi-task Candidates Selection for Various Context-Adaptive Conversational Retrieval

Hongru Wang, Boyang Xue, Baohang Zhou +5

Conversational retrieval refers to an information retrieval system that operates in an iterative and interactive manner, requiring the retrieval of various external resources, such…

cs.CL2024★ 1 cited

MlingConf: A Comprehensive Study of Multilingual Confidence Estimation on Large Language Models

Boyang Xue, Hongru Wang, Rui Wang +6

The tendency of Large Language Models (LLMs) to generate hallucinations raises concerns regarding their reliability. Therefore, confidence estimations indicating the extent of trus…

cs.CL2024

Self-DC: When to Reason and When to Act? Self Divide-and-Conquer for Compositional Unknown Questions

Hongru Wang, Boyang Xue, Baohang Zhou +5

Previous research has typically concentrated on leveraging the internal knowledge of Large Language Models (LLMs) to answer known questions (i.e., \textit{internal reasoning such a…