activity
20242026
most citedOpenAI GPT-5 System Card

17 citations · 17 across the 1 of their papers we have counts for

collaborators

8 papers

cs.CL202617 cited

OpenAI GPT-5 System Card

Aaditya Singh, Adam Fry, Adam Perelman +483

This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers most questions, a deeper reason…

cs.CY2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.AI2024

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…