6 citations · 9 across the 12 of their papers we have counts for
13 papers
FastLongSpeech: Enhancing Large Speech-Language Models for Efficient Long-Speech Processing
Shoutao Guo, Shaolei Zhang, Qingkai Fang +3
The rapid advancement of Large Language Models (LLMs) has spurred significant progress in Large Speech-Language Models (LSLMs), enhancing their capabilities in both speech understa…
FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented Generation
Zhuocheng Zhang, Yang Feng, Min Zhang
Retrieval-Augmented Generation (RAG) plays a pivotal role in modern large language model applications, with numerous existing frameworks offering a wide range of functionalities to…
LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented Searchers
Zhuocheng Zhang, Yang Feng, Min Zhang
Retrieval-Augmented Generation (RAG) is a crucial method for mitigating hallucinations in Large Language Models (LLMs) and integrating external knowledge into their responses. Exis…
Overcoming Non-monotonicity in Transducer-based Streaming Generation
Zhengrui Ma, Yang Feng, Min Zhang
Streaming generation models are utilized across fields, with the Transducer architecture being popular in industrial applications. However, its input-synchronous decoding mechanism…
Agent-SiMT: Agent-assisted Simultaneous Machine Translation with Large Language Models
Shoutao Guo, Shaolei Zhang, Zhengrui Ma +2
Simultaneous Machine Translation (SiMT) generates target translations while reading the source sentence. It relies on a policy to determine the optimal timing for reading sentences…
CTC-based Non-autoregressive Textless Speech-to-Speech Translation
Qingkai Fang, Zhengrui Ma, Yan Zhou +2
Direct speech-to-speech translation (S2ST) has achieved impressive translation quality, but it often faces the challenge of slow decoding due to the considerable length of speech s…
Can We Achieve High-quality Direct Speech-to-Speech Translation without Parallel Speech Data?
Qingkai Fang, Shaolei Zhang, Zhengrui Ma +2
Recently proposed two-pass direct speech-to-speech translation (S2ST) models decompose the task into speech-to-text translation (S2TT) and text-to-speech (TTS) within an end-to-end…
StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learning
Shaolei Zhang, Qingkai Fang, Shoutao Guo +3
Simultaneous speech-to-speech translation (Simul-S2ST, a.k.a streaming speech translation) outputs target speech while receiving streaming speech inputs, which is critical for real…
A Non-autoregressive Generation Framework for End-to-End Simultaneous Speech-to-Speech Translation
Zhengrui Ma, Qingkai Fang, Shaolei Zhang +3
Simultaneous translation models play a crucial role in facilitating communication. However, existing research primarily focuses on text-to-text or speech-to-text models, necessitat…
SiLLM: Large Language Models for Simultaneous Machine Translation
Shoutao Guo, Shaolei Zhang, Zhengrui Ma +2
Simultaneous Machine Translation (SiMT) generates translations while reading the source sentence, necessitating a policy to determine the optimal timing for reading and generating…
Addressing the Length Bias Problem in Document-Level Neural Machine Translation
Zhuocheng Zhang, Shuhao Gu, Min Zhang +1
Document-level neural machine translation (DNMT) has shown promising results by incorporating more context information. However, this approach also introduces a length bias problem…
Beyond MLE: Convex Learning for Text Generation
Chenze Shao, Zhengrui Ma, Min Zhang +1
Maximum likelihood estimation (MLE) is a statistical method used to estimate the parameters of a probability distribution that best explain the observed data. In the context of tex…
Non-autoregressive Streaming Transformer for Simultaneous Translation
Zhengrui Ma, Shaolei Zhang, Shoutao Guo +3
Simultaneous machine translation (SiMT) models are trained to strike a balance between latency and translation quality. However, training these models to achieve high quality while…