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cs.LG2026
ZOIF: Zeroth-Order Influence Function Estimation for LLM Data Selection Using Only Forward Passes
Lisong He, Yunxuan Jiang, Haishan Ye +1
Influence functions enable principled data selection for large language models (e.g., identifying influential training samples for model editing, debugging, or efficient fine-tunin…
cs.LG2024
Multi-view Disentanglement for Reinforcement Learning with Multiple Cameras
Mhairi Dunion, Stefano V. Albrecht
The performance of image-based Reinforcement Learning (RL) agents can vary depending on the position of the camera used to capture the images. Training on multiple cameras simultan…
cs.LG2023★ 1 cited
Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning
Trevor McInroe, Adam Jelley, Stefano V. Albrecht +1
Offline pretraining with a static dataset followed by online fine-tuning (offline-to-online, or OtO) is a paradigm well matched to a real-world RL deployment process. In this scena…