2026
Unlocking Full Efficiency of Token Filtering in Large Language Model Training
ICLR 2026poster
Token filtering has been proposed to enhance the utility of large language models (LLMs) by eliminating inconsequential tokens during training. While using fewer tokens is expected to reduce computational workloads, existing methods have not yet achieved a real-world efficiency boost. This is primar…