Papers by Ye Ziqi
Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for Ensembling (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) have demonstrated remarkable capabilities in a wide range of tasks and contexts. |
| Approach: | They propose to use a token-level ensembling method to exploit the probability information at each generation step and to avoid early incorrect tokens. |
| Outcome: | The proposed method breaks the existing community performance ceiling and improves on several benchmarks. |