most citedLLaMA-Omni2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech Synthesis

2 citations · 3 across the 3 of their papers we have counts for

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cs.CL2025

Inflated Excellence or True Performance? Rethinking Medical Diagnostic Benchmarks with Dynamic Evaluation

Xiangxu Zhang, Lei Li, Yanyun Zhou +3

Medical diagnostics is a high-stakes and complex domain that is critical to patient care. However, current evaluations of large language models (LLMs) remain limited in capturing k…

cs.CL20252 cited

LLaMA-Omni2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech Synthesis

Qingkai Fang, Yan Zhou, Shoutao Guo +2

Real-time, intelligent, and natural speech interaction is an essential part of the next-generation human-computer interaction. Recent advancements have showcased the potential of b…

cs.CL2024

BayLing 2: A Multilingual Large Language Model with Efficient Language Alignment

Shaolei Zhang, Kehao Zhang, Qingkai Fang +4

Large language models (LLMs), with their powerful generative capabilities and vast knowledge, empower various tasks in everyday life. However, these abilities are primarily concent…

cs.CL2024

Reverse Modeling in Large Language Models

Sicheng Yu, Yuanchen Xu, Cunxiao Du +5

Humans are accustomed to reading and writing in a forward manner, and this natural bias extends to text understanding in auto-regressive large language models (LLMs). This paper in…

cs.CL2024

LLaMA-Omni: Seamless Speech Interaction with Large Language Models

Qingkai Fang, Shoutao Guo, Yan Zhou +3

Models like GPT-4o enable real-time interaction with large language models (LLMs) through speech, significantly enhancing user experience compared to traditional text-based interac…