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Chanin Eom

2 accepted papers

2026

Post-Hoc Merging is Not Enough: Many-Shot Model Merging with Loss-Gap Balancing

ICML 2026poster

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, avoiding costly joint training. However, most existing approaches rely on post-hoc merging, in which task-specific models are merged …

Cited by 0SourceScholar
2024

AD4RL: Autonomous Driving Benchmarks for Offline Reinforcement Learning with Value-based Dataset

ICRA 2024poster

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, most algorithm development research in offline reinforcement learning still relies on game tasks with synthetic datasets…

Cited by 12SourceScholar