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cs.LG2025
A Unified Noise-Curvature View of Loss of Trainability
Gunbir Singh Baveja, Alex Lewandowski, Mark Schmidt
Loss of trainability refers to a phenomenon in continual learning where parameter updates no longer make progress on the optimization objective, so accuracy stalls or degrades as t…
cs.LG2024
BlockLLM: Memory-Efficient Adaptation of LLMs by Selecting and Optimizing the Right Coordinate Blocks
Amrutha Varshini Ramesh, Vignesh Ganapathiraman, Issam H. Laradji +1
Training large language models (LLMs) for pretraining or adapting to new tasks and domains has become increasingly critical as their applications expand. However, as the model and…