LoRIF exploits low-rank gradient structure to reduce storage and query I/O to O(c√D) and inverse Hessian memory to O(Dr), achieving up to 20× speedups over LoGRA at scale.
HiLight trains a lightweight actor via reinforcement learning to insert highlight tags around pivotal evidence spans in frozen LLM contexts, boosting reasoning without altering inputs or requiring evidence labels.
OmniGF unifies multi-person gaze following via dual-branch vision-language decoding with head embeddings, achieving state-of-the-art spatial, semantic, and social gaze reasoning.
RuleSmith uses multi-agent LLM self-play and Bayesian optimization to automatically balance complex games and find highly balanced rule configurations.