From the 1 of 4 linked papers with an AI index.
4 papers
Reasoning Jury: Multi-Model Consensus for Evaluating Reasoning Traces
Congchao Wang, Diwakar Singh, Qiaozi Gao +3
Improving reasoning LLMs requires the ability to judge the quality of long reasoning traces for effective reasoning data curation, strong training signals during reinforcement lear…
A Threshold Exceedance Framework for CBRN Uplift Evaluation in Frontier Language Models
Rahul Gupta, Abhinav Mohanty, Payal Motwani +8
The paper introduces a Threshold Exceedance Criteria (TEC) framework to systematically evaluate whether frontier language models increase a non‑expert's ability to plan chemical, b…
Evaluating Nova 2.0 Lite model under Amazon's Frontier Model Safety Framework
Satyapriya Krishna, Matteo Memelli, Tong Wang +5
Amazon published its Frontier Model Safety Framework (FMSF) as part of the Paris AI summit, following which we presented a report on Amazon's Premier model. In this report, we pres…
D-REX: A Benchmark for Detecting Deceptive Reasoning in Large Language Models
Satyapriya Krishna, Andy Zou, Rahul Gupta +6
The safety and alignment of Large Language Models (LLMs) are critical for their responsible deployment. Current evaluation methods predominantly focus on identifying and preventing…