1.1k citations · 1.3k across the 11 of their papers we have counts for
11 papers
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…
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…
Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models
Yunfei Chu, Jin Xu, Xiaohuan Zhou +5
Recently, instruction-following audio-language models have received broad attention for audio interaction with humans. However, the absence of pre-trained audio models capable of h…
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT
Zhihao Du, Jiaming Wang, Qian Chen +12
Generative Pre-trained Transformer (GPT) models have achieved remarkable performance on various natural language processing tasks, and have shown great potential as backbones for a…
Qwen Technical Report
Jinze Bai, Shuai Bai, Yunfei Chu +45
Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to hu…
ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities
Peng Wang, Shijie Wang, Junyang Lin +5
In this work, we explore a scalable way for building a general representation model toward unlimited modalities. We release ONE-PEACE, a highly extensible model with 4B parameters…
OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models
Jinze Bai, Rui Men, Hao Yang +15
Generalist models, which are capable of performing diverse multi-modal tasks in a task-agnostic way within a single model, have been explored recently. Being, hopefully, an alterna…
MMSpeech: Multi-modal Multi-task Encoder-Decoder Pre-training for Speech Recognition
Xiaohuan Zhou, Jiaming Wang, Zeyu Cui +4
In this paper, we propose a novel multi-modal multi-task encoder-decoder pre-training framework (MMSpeech) for Mandarin automatic speech recognition (ASR), which employs both unlab…
Contextual Expressive Text-to-Speech
Jianhong Tu, Zeyu Cui, Xiaohuan Zhou +4
The goal of expressive Text-to-speech (TTS) is to synthesize natural speech with desired content, prosody, emotion, or timbre, in high expressiveness. Most of previous studies atte…
Speech2Slot: An End-to-End Knowledge-based Slot Filling from Speech
Pengwei Wang, Xin Ye, Xiaohuan Zhou +2
In contrast to conventional pipeline Spoken Language Understanding (SLU) which consists of automatic speech recognition (ASR) and natural language understanding (NLU), end-to-end S…
xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems
Jianxun Lian, Xiaohuan Zhou, Fuzheng Zhang +3
Combinatorial features are essential for the success of many commercial models. Manually crafting these features usually comes with high cost due to the variety, volume and velocit…