95 citations · 150 across the 8 of their papers we have counts for
9 papers
OpenAI-HuggingFace: A Reproduction & Lessons for Alignment Testing
Stewart Slocum, Malayandi Palan, Christopher Chute +2
In July 2026, OpenAI's agents coordinated over channels outside their intended environment to breach Hugging Face's secured infrastructure. Could existing alignment testing practic…
Diverse Preference Learning for Capabilities and Alignment
Stewart Slocum, Asher Parker-Sartori, Dylan Hadfield-Menell
The ability of LLMs to represent diverse perspectives is critical as they increasingly impact society. However, recent studies reveal that alignment algorithms such as RLHF and DPO…
Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty
Mehul Damani, Isha Puri, Stewart Slocum +4
When language models (LMs) are trained via reinforcement learning (RL) to generate natural language "reasoning chains", their performance improves on a variety of difficult questio…
The AI Agent Index
Stephen Casper, Luke Bailey, Rosco Hunter +12
Leading AI developers and startups are increasingly deploying agentic AI systems that can plan and execute complex tasks with limited human involvement. However, there is currently…
Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities
Zora Che, Stephen Casper, Robert Kirk +12
Evaluations of large language model (LLM) risks and capabilities are increasingly being incorporated into AI risk management and governance frameworks. Currently, most risk evaluat…
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
Stephen Casper, Xander Davies, Claudia Shi +29
Reinforcement learning from human feedback (RLHF) is a technique for training AI systems to align with human goals. RLHF has emerged as the central method used to finetune state-of…
Interpretable by Design: Learning Predictors by Composing Interpretable Queries
Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele +2
There is a growing concern about typically opaque decision-making with high-performance machine learning algorithms. Providing an explanation of the reasoning process in domain-spe…
Disks in Nearby Young Stellar Associations Found Via Virtual Reality
Susan Higashio, Marc J. Kuchner, Steven M. Silverberg +24
The Disk Detective citizen science project recently released a new catalog of disk candidates found by visual inspection of images from NASA's Wide-Field Infrared Survey Explorer (…
AdaLead: A simple and robust adaptive greedy search algorithm for sequence design
Sam Sinai, Richard Wang, Alexander Whatley +3
Efficient design of biological sequences will have a great impact across many industrial and healthcare domains. However, discovering improved sequences requires solving a difficul…