4 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
Beyond the Safety Bundle: Auditing the Helpful and Harmless Dataset
Khaoula Chehbouni, Jonathan Colaço Carr, Yash More +2
In an effort to mitigate the harms of large language models (LLMs), learning from human feedback (LHF) has been used to steer LLMs towards outputs that are intended to be both less…
Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs
Megh Thakkar, Quentin Fournier, Matthew Riemer +4
There is a growing interest in training domain-expert LLMs that excel in specific technical fields compared to their general-purpose instruction-tuned counterparts. However, these…
Trust No Bot: Discovering Personal Disclosures in Human-LLM Conversations in the Wild
Niloofar Mireshghallah, Maria Antoniak, Yash More +2
Measuring personal disclosures made in human-chatbot interactions can provide a better understanding of users' AI literacy and facilitate privacy research for large language models…
Towards More Realistic Extraction Attacks: An Adversarial Perspective
Yash More, Prakhar Ganesh, Golnoosh Farnadi
Language models are prone to memorizing their training data, making them vulnerable to extraction attacks. While existing research often examines isolated setups, such as a single…