Papers with large-scale LLM data reweighting
ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting (2025.acl-long)
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Rui Pan, Dylan Zhang, Hanning Zhang, Xingyuan Pan, Minrui Xu, Jipeng Zhang, Renjie Pi, Xiaoyu Wang, Tong Zhang
| Challenge: | Existing paradigms for bilevel optimization require second-order information, making it difficult to scale them up. |
| Approach: | They propose a scalable instantiation of a bilevel optimization paradigm for large-scale LLMs by using a memory-efficient training technique. |
| Outcome: | The proposed paradigm scales to 30B-sized LLMs on 8H100 GPUs. |