24 citations · 45 across the 8 of their papers we have counts for
9 papers
Reinforcement Learning Towards Broadly and Persistently Beneficial Models
Akshay V. Jagadeesh, Rahul K. Arora, Khaled Saab +5
As AI systems are deployed across increasingly diverse and high-stakes settings, model alignment must generalize beyond the tasks and domains seen during training. This is especial…
HealthBench Professional: Evaluating Large Language Models on Real Clinician Chats
Rebecca Soskin Hicks, Mikhail Trofimov, Dominick Lim +13
Millions of clinicians use ChatGPT to support clinical care, but evaluations of the most common use cases in model-clinician conversations are limited. We introduce HealthBench Pro…
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…
gpt-oss-120b & gpt-oss-20b Model Card
OpenAI, :, Sandhini Agarwal +124
We present gpt-oss-120b and gpt-oss-20b, two open-weight reasoning models that push the frontier of accuracy and inference cost. The models use an efficient mixture-of-expert trans…
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…
Go-Oracle: Automated Test Oracle for Go Concurrency Bugs
Foivos Tsimpourlas, Chao Peng, Carlos Rosuero +2
The Go programming language has gained significant traction for developing software, especially in various infrastructure systems. Nonetheless, concurrency bugs have become a preva…
BenchDirect: A Directed Language Model for Compiler Benchmarks
Foivos Tsimpourlas, Pavlos Petoumenos, Min Xu +4
The exponential increase of hardware-software complexity has made it impossible for compiler engineers to find the right optimization heuristics manually. Predictive models have be…
BenchPress: A Deep Active Benchmark Generator
Foivos Tsimpourlas, Pavlos Petoumenos, Min Xu +4
We develop BenchPress, the first ML benchmark generator for compilers that is steerable within feature space representations of source code. BenchPress synthesizes compiling functi…
Learning to Encode and Classify Test Executions
Foivos Tsimpourlas, Ajitha Rajan, Miltiadis Allamanis
The challenge of automatically determining the correctness of test executions is referred to as the test oracle problem and is one of the key remaining issues for automated testing…