24 citations · 39 across the 6 of their papers we have counts for
6 papers
From Hard Refusals to Safe-Completions: Toward Output-Centric Safety Training
Yuan Yuan, Tina Sriskandarajah, Anna-Luisa Brakman +4
Large Language Models used in ChatGPT have traditionally been trained to learn a refusal boundary: depending on the user's intent, the model is taught to either fully comply or out…
Balancing Knowledge Delivery and Emotional Comfort in Healthcare Conversational Systems
Shang-Chi Tsai, Yun-Nung Chen
With the advancement of large language models, many dialogue systems are now capable of providing reasonable and informative responses to patients' medical conditions. However, whe…
HealthBench: Evaluating Large Language Models Towards Improved Human Health
Rahul K. Arora, Jason Wei, Rebecca Soskin Hicks +9
We present HealthBench, an open-source benchmark measuring the performance and safety of large language models in healthcare. HealthBench consists of 5,000 multi-turn conversations…
Deliberative Alignment: Reasoning Enables Safer Language Models
Melody Y. Guan, Manas Joglekar, Eric Wallace +12
As large-scale language models increasingly impact safety-critical domains, ensuring their reliable adherence to well-defined principles remains a fundamental challenge. We introdu…
Rule Based Rewards for Language Model Safety
Tong Mu, Alec Helyar, Johannes Heidecke +7
Reinforcement learning based fine-tuning of large language models (LLMs) on human preferences has been shown to enhance both their capabilities and safety behavior. However, in cas…
VISTA: A Visual and Textual Attention Dataset for Interpreting Multimodal Models
Harshit, Tolga Tasdizen
The recent developments in deep learning led to the integration of natural language processing (NLP) with computer vision, resulting in powerful integrated Vision and Language Mode…