4 citations · 16 across the 43 of their papers we have counts for
5 papers · 1 filter
Towards Context-Invariant Safety Alignment for Large Language Models
Yixu Wang, Yang Yao, Xin Wang +4
Preference-based post-training aligns LLMs with human intent, yet safety behavior often remains brittle. A model may refuse a harmful request in a standard prompt but comply when t…
Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks
Yixin Cao, Shibo Hong, Xinze Li +24
Large Language Models (LLMs) are advancing at an amazing speed and have become indispensable across academia, industry, and daily applications. To keep pace with the status quo, th…
Identity Lock: Locking API Fine-tuned LLMs With Identity-based Wake Words
Hongyu Su, Yifeng Gao, Yifan Ding +1
The rapid advancement of Large Language Models (LLMs) has increased the complexity and cost of fine-tuning, leading to the adoption of API-based fine-tuning as a simpler and more e…
Whose Side Are You On? Investigating the Political Stance of Large Language Models
Pagnarasmey Pit, Xingjun Ma, Mike Conway +6
Large Language Models (LLMs) have gained significant popularity for their application in various everyday tasks such as text generation, summarization, and information retrieval. A…
Fake Alignment: Are LLMs Really Aligned Well?
Yixu Wang, Yan Teng, Kexin Huang +7
The growing awareness of safety concerns in large language models (LLMs) has sparked considerable interest in the evaluation of safety. This study investigates an under-explored is…