---
title: "Tao Ge — papers of 2023 — 3 papers, the most cited first"
description: "Tao Ge — papers of 2023: 3 papers on Elamur Research, the most cited first — what each work is about in our own words."
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# Tao Ge — papers of 2023 — 3 papers, the most cited first

3 papers · [all years of Tao Ge](https://md.research.elamur.ai/free/en/authors/tao-ge/#years)

- [Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration arXiv:2307.05300](https://md.research.elamur.ai/free/en/papers/wang-2023-unleashing-emergent-cognitive-synergy-large/) — Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al. · 2023 · 140 citations
- [In-context Autoencoder for Context Compression in a Large Language Model arXiv:2307.06945](https://md.research.elamur.ai/free/en/papers/ge-2023-context-autoencoder-context-compression-large/) — Tao Ge, Jing Hu, Lei Wang, et al. · 2023 · 114 citations

**[Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation](https://md.research.elamur.ai/free/en/papers/xia-2023-speculative-decoding-exploiting-speculative-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Heming Xia, Tao Ge, Peiyi Wang, et al.*2023 · 103 citations*