110 citations · 196 across the 15 of their papers we have counts for
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cs.LG2026
Breaking Entropy Bounds: Accelerating RL Training via MTP with Rejection Sampling
Yucheng Li, Huiqiang Jiang, Yang Xu +14
Reinforcement learning (RL) has become a key component in modern large language models, yet the rollout stage remains the key bottleneck in RL training pipelines. Although Multi-To…
cs.LG2024
A Unified View of Delta Parameter Editing in Post-Trained Large-Scale Models
Qiaoyu Tang, Le Yu, Bowen Yu +5
Post-training has emerged as a crucial paradigm for adapting large-scale pre-trained models to various tasks, whose effects are fully reflected by delta parameters (i.e., the dispa…
cs.LG2024
Transferable Post-training via Inverse Value Learning
Xinyu Lu, Xueru Wen, Yaojie Lu +6
As post-training processes utilize increasingly large datasets and base models continue to grow in size, the computational demands and implementation challenges of existing algorit…