Biao Tian

Qwen-Audio-3.1-ASR Technical Report

We present Qwen-Audio-3.1-ASR, a family of audio-language models that builds upon its predecesor Qwen-Audio-3.0-ASR with improved speech recognition and expanded capabilities in speaker-diarized transcription and general audio understanding. The family retains support for 30 languages and 16 Chinese dialects, together...

The Platonic brain bridge hypothesis: human brain networks as an architectural prior for omni models

Listen, Do Not Copy: Internalizing Audio-Grounded Scaffold Context for Robust Omni-Model Speech Understanding

A joint GDPO task in which the model learns when to use a clue and how to produce a speaker-attributed transcript from separately normalized format, gate, and transcript rewards is formulated.

The Platonic brain bridge hypothesis: human brain networks as an architectural prior for multimodal large language models

The Platonic brain bridge hypothesis is proposed: omni models, multimodal large language models that process video, audio and text jointly, converge on brain-like representations usable in both directions, and human brain organization is a usable architectural prior for multimodal large language models.

Qwen-Audio-3.0-ASR Technical Report

Qwen-Audio-3.0-ASR is presented, a Mixture-of-Experts (MoE) LLM-based ASR system designed to address production demands through a unified, instruction-following framework and demonstrates state-of-the-art or highly competitive recognition performance across a broad range of evaluation conditions.