2 papers
cs.LG2026
Dynamic Weight Grafting: Localizing Finetuned Factual Knowledge in Transformers
Todd Nief, David Reber, Sean Richardson +1
When an LLM learns a new fact during finetuning (e.g., new movie releases, newly elected pope, etc.), where does this information go? Are entities enriched with relation informatio…
cs.CL2025
RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals
David Reber, Sean Richardson, Todd Nief +2
Reward models are widely used as proxies for human preferences when aligning or evaluating LLMs. However, reward models are black boxes, and it is often unclear what, exactly, they…