activity
20232025
most citedGödel Agent: A Self-Referential Agent Framework for Recursive Self-Improvement

2 citations · 6 across the 15 of their papers we have counts for

collaborators
Showing 2024 · cs.CLShow all

6 papers · 2 filters

cs.CL2024★ 1 cited

DSGram: Dynamic Weighting Sub-Metrics for Grammatical Error Correction in the Era of Large Language Models

Jinxiang Xie, Yilin Li, Xunjian Yin +1

Evaluating the performance of Grammatical Error Correction (GEC) models has become increasingly challenging, as large language model (LLM)-based GEC systems often produce correctio…

cs.CL2024

Evaluating Self-Generated Documents for Enhancing Retrieval-Augmented Generation with Large Language Models

Jiatao Li, Xinyu Hu, Xunjian Yin +1

The integration of documents generated by LLMs themselves (Self-Docs) alongside retrieved documents has emerged as a promising strategy for retrieval-augmented generation systems.…

cs.CL2024

SMART-RAG: Selection using Determinantal Matrices for Augmented Retrieval

Jiatao Li, Xinyu Hu, Xiaojun Wan

Retrieval-Augmented Generation (RAG) has greatly improved large language models (LLMs) by enabling them to generate accurate, contextually grounded responses through the integratio…

cs.CL2024

ContraSolver: Self-Alignment of Language Models by Resolving Internal Preference Contradictions

Xu Zhang, Xunjian Yin, Xiaojun Wan

While substantial advancements have been made in developing large language models (LLMs), achieving control over their behavior can be difficult. Direct preference optimization (DP…

cs.CL2024

Enhancing Jailbreak Attacks with Diversity Guidance

Xu Zhang, Dinghao Jing, Xiaojun Wan

As large language models(LLMs) become commonplace in practical applications, the security issues of LLMs have attracted societal concerns. Although extensive efforts have been made…

cs.CL2024

Benchmarking Knowledge Boundary for Large Language Models: A Different Perspective on Model Evaluation

Xunjian Yin, Xu Zhang, Jie Ruan +1

In recent years, substantial advancements have been made in the development of large language models, achieving remarkable performance across diverse tasks. To evaluate the knowled…