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20162023
most citedPhoenix: Democratizing ChatGPT across Languages

20 citations · 133 across the 27 of their papers we have counts for

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7 papers · 1 filter

cs.CL202320 cited

HuatuoGPT, towards Taming Language Model to Be a Doctor

Hongbo Zhang, Junying Chen, Feng Jiang +10

In this paper, we present HuatuoGPT, a large language model (LLM) for medical consultation. The core recipe of HuatuoGPT is to leverage both \textit{distilled data from ChatGPT} an…

cs.CL2023

Topic-driven Distant Supervision Framework for Macro-level Discourse Parsing

Feng Jiang, Longwang He, Peifeng Li +2

Discourse parsing, the task of analyzing the internal rhetorical structure of texts, is a challenging problem in natural language processing. Despite the recent advances in neural…

cs.CL2023

Dynamic Transformers Provide a False Sense of Efficiency

Yiming Chen, Simin Chen, Zexin Li +4

Despite much success in natural language processing (NLP), pre-trained language models typically lead to a high computational cost during inference. Multi-exit is a mainstream appr…

cs.CL202320 cited

Phoenix: Democratizing ChatGPT across Languages

Zhihong Chen, Feng Jiang, Junying Chen +11

This paper presents our efforts to democratize ChatGPT across language. We release a large language model "Phoenix", achieving competitive performance among open-source English and…

cs.CL201912 cited

VQVAE Unsupervised Unit Discovery and Multi-scale Code2Spec Inverter for Zerospeech Challenge 2019

Andros Tjandra, Berrak Sisman, Mingyang Zhang +3

We describe our submitted system for the ZeroSpeech Challenge 2019. The current challenge theme addresses the difficulty of constructing a speech synthesizer without any text or ph…

cs.CL2018

On the End-to-End Solution to Mandarin-English Code-switching Speech Recognition

Zhiping Zeng, Yerbolat Khassanov, Van Tung Pham +3

Code-switching (CS) refers to a linguistic phenomenon where a speaker uses different languages in an utterance or between alternating utterances. In this work, we study end-to-end…