Akash Srivastava

We introduce a Particle Filtering approach to Inference Scaling that is robust against inherently imperfect reward models and performs significantly better than previous methods.

AIM introduces a new scheme to improve merging performance in LLMs by combining continual learning principles and activation space-based model compression.