Papers by Gautam Rajendrakumar Gare
Activation Reward Models for Few-Shot Model Alignment (2026.findings-acl)
Copied to clipboard
Tianning Chai, Chancharik Mitra, Brandon Huang, Gautam Rajendrakumar Gare, Zhiqiu Lin, Assaf Arbelle, Leonid Karlinsky, Rogerio Feris, Trevor Darrell, Deva Ramanan, Roei Herzig
| Challenge: | A common approach is to use reward models that enable reinforcement-learning post-training. |
| Approach: | They propose a method that steers LLM activations to align with few-shot preference data without finetuning. |
| Outcome: | The proposed method surpasses zero-shot, few-shot and voting-based benchmarks on reward hacking and noise signals. |