Ge, Tao
Microsoft Research Asia (China)
4 papers on CoChatORCID 0000-0002-6630-634X
Most cited papers
- Verified
Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation
Xia, H., Ge, T., Wang, P., Chen, S.-Q., Wei, F., & Sui, Z. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023
Natural Language Processing TechniquesTopic Modeling
Cited by 40
- Verified
In-context Autoencoder for Context Compression in a Large Language Model
Ge, T., Hu, J., Wang, L., Wang, X., Chen, S.-Q., & Wei, F. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 11
- Verified
Lossless Acceleration for Seq2seq Generation with Aggressive Decoding
Ge, T., Xia, H., Sun, X., Chen, S.-Q., & Wei, F. (2022) · arXiv
Natural Language Processing TechniquesTopic Modeling
Cited by 6
- Verified
ALYMPICS: LLM Agents Meet Game Theory -- Exploring Strategic Decision-Making with AI Agents
Mao, S., Cai, Y., Xia, Y., Wu, W., Wang, X., Wang, F., Ge, T., & Wei, F. (2023) · arXiv
Game Theory and ApplicationsArtificial Intelligence in Games
Cited by 3
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