2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2025★ 2 cited
Shallow Robustness, Deep Vulnerabilities: Multi-Turn Evaluation of Medical LLMs
Blazej Manczak, Eric Lin, Francisco Eiras +2
Large language models (LLMs) are rapidly transitioning into medical clinical use, yet their reliability under realistic, multi-turn interactions remains poorly understood. Existing…
cs.AI2025
The Singapore Consensus on Global AI Safety Research Priorities
Yoshua Bengio, Tegan Maharaj, Luke Ong +84
Rapidly improving AI capabilities and autonomy hold significant promise of transformation, but are also driving vigorous debate on how to ensure that AI is safe, i.e., trustworthy,…
cs.LG2025★ 1 cited
Know Thy Judge: On the Robustness Meta-Evaluation of LLM Safety Judges
Francisco Eiras, Eliott Zemour, Eric Lin +1
Large Language Model (LLM) based judges form the underpinnings of key safety evaluation processes such as offline benchmarking, automated red-teaming, and online guardrailing. This…