activity
20232026
most citedQwen2 Technical Report

60 citations · 111 across the 12 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

eess.AS2024★ 2 cited

WavChat: A Survey of Spoken Dialogue Models

Shengpeng Ji, Yifu Chen, Minghui Fang +16

Recent advancements in spoken dialogue models, exemplified by systems like GPT-4o, have captured significant attention in the speech domain. Compared to traditional three-tier casc…

eess.AS2024

Analyzing and Mitigating Inconsistency in Discrete Audio Tokens for Neural Codec Language Models

Wenrui Liu, Zhifang Guo, Jin Xu +4

Building upon advancements in Large Language Models (LLMs), the field of audio processing has seen increased interest in training audio generation tasks with discrete audio token s…

cs.CL2024★ 1 cited

Leveraging Annotator Disagreement for Text Classification

Jin Xu, Mariët Theune, Daniel Braun

It is common practice in text classification to only use one majority label for model training even if a dataset has been annotated by multiple annotators. Doing so can remove valu…

eess.AS2024★ 7 cited

Qwen2-Audio Technical Report

Yunfei Chu, Jin Xu, Qian Yang +9

We introduce the latest progress of Qwen-Audio, a large-scale audio-language model called Qwen2-Audio, which is capable of accepting various audio signal inputs and performing audi…

cs.CL2024★ 60 cited

Qwen2 Technical Report

An Yang, Baosong Yang, Binyuan Hui +59

This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models. We release a comprehensive suite of foundational and instruct…

eess.AS2024

AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehension

Qian Yang, Jin Xu, Wenrui Liu +8

Recently, instruction-following audio-language models have received broad attention for human-audio interaction. However, the absence of benchmarks capable of evaluating audio-cent…