activity
20222026
most citedEvaluating Hallucinations in Chinese Large Language Models

8 citations · 24 across the 34 of their papers we have counts for

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12 papers · 1 filter

cs.CL2026

XTurnix: Large-Scale Self-Supervised Turn Control through Two-State Binary Decisions

Zhanxun Liu, Yifan Duan, Hengtao Wu +7

General turn-taking behavior in real-time dialogue systems requires deciding whether to keep listening or start responding while listening, and whether to continue or stop while sp…

cs.CV2026

MOSS-VL Technical Report

Pengyu Wang, Chenkun Tan, Shaojun Zhou +29

We present MOSS-VL, an open vision-language model family that treats real-time interaction -- perceiving while it speaks -- as a first-class capability. It is co-designed across th…

cs.SD2026

OmniVAE: An Audio-Video VAE with Cross-Modal Alignment for Joint Generation

Jun Zhan, Chen Yang, Yitian Gong +23

Recent generative models are moving beyond silent video or standalone audio synthesis toward the joint generation of synchronized audio and video. Despite this progress, jointly ge…

cs.SD2026

MOSS-Audio Technical Report

Chen Yang, Chufan Yu, Hanfu Chen +27

MOSS-Audio is a unified audio-language model for speech, environmental sound, and music understanding, supporting audio captioning, time-aware question answering, timestamped trans…

cs.SD2026

X-Voice: Enabling Everyone to Speak 30 Languages via Zero-Shot Cross-Lingual Voice Cloning

Rixi Xu, Qingyu Liu, Haitao Li +10

In this paper, we present X-Voice, a 0.4B multilingual zero-shot voice cloning model that clones arbitrary voices and enables everyone to speak 30 languages. X-Voice is trained on…

cs.SD2026

MOSS-VoiceGenerator: Create Realistic Voices with Natural Language Descriptions

Kexin Huang, Liwei Fan, Botian Jiang +11

Voice design from natural language aims to generate speaker timbres directly from free-form textual descriptions, allowing users to create voices tailored to specific roles, person…

cs.SD2026

MOSS-TTSD: Text to Spoken Dialogue Generation

Yuqian Zhang, Donghua Yu, Zhengyuan Lin +15

Spoken dialogue generation is crucial for applications like podcasts, dynamic commentary, and entertainment content, but poses significant challenges compared to single-utterance t…

cs.SD2026

MOSS-TTS Technical Report

Yitian Gong, Botian Jiang, Yiwei Zhao +23

This technical report presents MOSS-TTS, a speech generation foundation model built on a scalable recipe: discrete audio tokens, autoregressive modeling, and large-scale pretrainin…

cs.CL2026

AI Can Learn Scientific Taste

Jingqi Tong, Mingzhe Li, Hangcheng Li +20

Scientific discovery depends on expert judgement and foresight, which we call scientific taste: the ability to judge and propose research ideas with the potential for long-term sci…

cs.CV2026★ 1 cited

MOVA: Towards Scalable and Synchronized Video-Audio Generation

OpenMOSS Team, Donghua Yu, Mingshu Chen +38

Audio is indispensable for real-world video, yet generation models have largely overlooked audio components. Current approaches to producing audio-visual content often rely on casc…

cs.CL2026

WESR: Scaling and Evaluating Word-level Event-Speech Recognition

Chenchen Yang, Kexin Huang, Liwei Fan +8

Speech conveys not only linguistic information but also rich non-verbal vocal events such as laughing and crying. While semantic transcription is well-studied, the precise localiza…

cs.SD2026

MOSS Transcribe Diarize Technical Report

MOSI. AI, :, Donghua Yu +23

Speaker-Attributed, Time-Stamped Transcription (SATS) aims to transcribe what is said and to precisely determine the timing of each speaker, which is particularly valuable for meet…