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cs.LG2026
Label-Free Reinforcement Learning via Cross-Model Entropy
Matt Gorbett, Hossein Shirazi
Post-training large language models with reinforcement learning is bottlenecked by the reward signal. Existing approaches require either ground-truth verifiable rewards, restrictin…
cs.AI2026
Cross-Model Disagreement as a Label-Free Correctness Signal
Matt Gorbett, Suman Jana
Detecting when a language model is wrong without ground truth labels is a fundamental challenge for safe deployment. Existing approaches rely on a model's own uncertainty -- such a…
cs.AI2026
Ventriloquist LLMs: Linear Alignment of Late-Stage Representations
Matt Gorbett, Suman Jana
Independently trained language models often learn compatible late-stage representations, despite differences in training objectives, architectures, and data modalities. We ask how…