4 papers
When Context Misleads: Intent-Guided Decoding for Robust Retrieval-Augmented Generation
Haolin Jin, Pengyue Yang, Huaming Chen
Retrieval-augmented generation (RAG) improves large language models by grounding generation in external evidence, but it also introduces a source trust problem: retrieved context m…
Trust in One Round: Confidence Estimation for Large Language Models via Structural Signals
Pengyue Yang, Jiawen Wen, Haolin Jin +3
Large language models (LLMs) are increasingly deployed in domains where errors carry high social, scientific, or safety costs. Yet standard confidence estimators, such as token lik…
Human-aligned AI Model Cards with Weighted Hierarchy Architecture
Pengyue Yang, Haolin Jin, Qingwen Zeng +3
The proliferation of Large Language Models (LLMs) has led to a burgeoning ecosystem of specialized, domain-specific models. While this rapid growth accelerates innovation, it has s…
The Tower of Babel Revisited: Multilingual Jailbreak Prompts on Closed-Source Large Language Models
Linghan Huang, Haolin Jin, Zhaoge Bi +6
Large language models (LLMs) have seen widespread applications across various domains, yet remain vulnerable to adversarial prompt injections. While most existing research on jailb…