2 papers
cs.AI2026
Post-Hoc Merging is Not Enough: Many-Shot Model Merging with Loss-Gap Balancing
Kyungjin Im, Miru Kim, Chanin Eom +1
Model merging has become a practical post-training strategy for building a single multi-task large language model (LLM) by combining multiple task-specialized models. However, most…
cs.LG2024
AD4RL: Autonomous Driving Benchmarks for Offline Reinforcement Learning with Value-based Dataset
Dongsu Lee, Chanin Eom, Minhae Kwon
Offline reinforcement learning has emerged as a promising technology by enhancing its practicality through the use of pre-collected large datasets. Despite its practical benefits,…