2 papers
cs.CL2026
From Token Probabilities to Semantic Constraints: Towards Declarative Probabilistic Evaluation of Language Models
Kyle Richardson, Cullen Anderson, Pranav Balakrishnan +4
While Large Language Models have improved rapidly, many fundamental questions remain about how to evaluate the knowledge and reasoning abilities they acquire, and how such evaluati…
cs.LG2026
Understanding and Mitigating Dataset Corruption in LLM Steering
Cullen Anderson, Narmeen Oozeer, Foad Namjoo +3
Contrastive steering has been shown as a simple and effective method to adjust the generative behavior of LLMs at inference time. It uses examples of prompt responses with and with…