28 citations · 52 across the 23 of their papers we have counts for
5 papers · 1 filter
SAR-LM: Symbolic Audio Reasoning with Large Language Models
Termeh Taheri, Yinghao Ma, Emmanouil Benetos
Large language models (LLMs) have advanced in text and vision, but their reasoning on audio remains limited. Most existing methods rely on dense audio embeddings, which are difficu…
CMI-Bench: A Comprehensive Benchmark for Evaluating Music Instruction Following
Yinghao Ma, Siyou Li, Juntao Yu +2
Recent advances in audio-text large language models (LLMs) have opened new possibilities for music understanding and generation. However, existing benchmarks are limited in scope,…
MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mix
Ziyang Ma, Yinghao Ma, Yanqiao Zhu +31
We introduce MMAR, a new benchmark designed to evaluate the deep reasoning capabilities of Audio-Language Models (ALMs) across massive multi-disciplinary tasks. MMAR comprises 1,00…
YuE: Scaling Open Foundation Models for Long-Form Music Generation
Ruibin Yuan, Hanfeng Lin, Shuyue Guo +55
We tackle the task of long-form music generation--particularly the challenging \textbf{lyrics-to-song} problem--by introducing YuE, a family of open foundation models based on the…
Audio-FLAN: An Instruction-Following Dataset for Unified Audio Understanding and Generation of Speech, Music, and Sound
Liumeng Xue, Ziya Zhou, Jiahao Pan +20
Recent advancements in audio tokenization have significantly enhanced the integration of audio capabilities into large language models (LLMs). However, audio understanding and gene…