arXiv AI August 10, 2026 By Haolong Zheng, Siyin Wang, Zengrui Jin, Mark Hasegawa-Johnson

MetaSICL: Globalizing Auditory LLMs for Underserved Speakers and Languages via Meta Speech In-Context Learning

arXiv:2601. 18904v3 Announce Type: replace-cross Abstract: Generative AI for speech and audio is increasingly expected to serve users across languages, cultures, and communities, yet current auditory Large Language Models (LLMs) are still largely trained and evaluated on high-resource data.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 3

FSA-GRPO: Teaching Auditory LLMs to Use Few-shot Demonstrations

arXiv:2606. 02615v1 Announce Type: cross Abstract: Few-shot prompting provides an effective way to adapt auditory large language models to low-resource tasks such as children's speech recognition.

By Haolong Zheng, Siyin Wang, Xulin Fan, Zengrui Jin, Mark Hasegawa-Johnson

llms reinforcement-learning multimodal

arXiv AI

Jul 14

Encoder-Side Neuron Identification and Amplification for Acoustic Perception in Large Audio-Language Models

arXiv:2607. 11801v1 Announce Type: cross Abstract: Large audio-language models (LALMs) often underperform on fine-grained, non-semantic attributes of speech, such as a speaker's emotion, despite strong performance on speech content.

By Yu-Han Huang, Chih-Kai Yang, Ke-Han Lu, An-Yu Cheng, Hung-yi Lee

llms fine-tuning

arXiv AI

Jul 7

Unified Audio Intelligence Without Regressing on Text Intelligence

arXiv:2607. 05196v1 Announce Type: cross Abstract: Audio intelligence involves understanding, reasoning about, and generating both audio and speech.

By Zhifeng Kong, Sang-gil Lee, Jaehyeon Kim, Boxin Wang, Zihan Liu, Sungwon Kim, Yang Chen, Arushi Goel, Rajarshi Roy, Wenliang Dai, Zhuolin Yang, Yangyi Chen, Dongfu Jiang, Sreyan Ghosh, Tuomas Rintamaki, Andrew Tao, Jonathan Raiman, Mohammad Shoeybi, Bryan Catanzaro, Wei Ping

llms rag agents reinforcement-learning efficiency multimodal benchmarks safety

arXiv AI

Aug 11

VoxZip: Semantic-Anchored Temporal KV Cache Compression for Long-Context Audio Inference

arXiv:2608. 08569v1 Announce Type: new Abstract: Recent advancements in Speech Large Language Models have demonstrated remarkable capabilities in understanding complex audio tasks.

By Wenxu Jia, Dongjie Fu, Xize Cheng, Fangming Feng, Linjun Li, Wenshi Chen, Yingming Li, Zhou Zhao, Tao Jin

llms efficiency multimodal benchmarks safety

arXiv Machine Learning

Jul 24

X$^3$-OPD: Distilling Reasoning into Large Audio-Language Models via On-Policy Alignment

arXiv:2607. 21550v1 Announce Type: new Abstract: While large audio-language models have achieved remarkable progress in auditory perception, they still lag behind text-based large language models in deep logical reasoning, primarily due to the scarcity of high-quality audio reasoning data.

By Dongjie Fu, Di Cao, Xize Cheng, Zihan Zhang, Wenxu Jia, Yifu Chen, Shengpeng Ji, Yu Zhang, Tao Jin

llms efficiency multimodal safety

arXiv AI

Jun 9

GenTSE: Enhancing Target Speaker Extraction via a Coarse-to-Fine Generative Language Model

arXiv:2512. 20978v2 Announce Type: replace-cross Abstract: Language Model (LM)-based generative modeling has emerged as a promising direction for TSE, offering potential for improved generalization and high-fidelity speech.

By Haoyang Li, Xuyi Zhuang, Azmat Adnan, Ye Ni, Wei Rao, Shreyas Gopal, Eng Siong Chng, Boon Siew Han, Yuanjin Zheng

llms rag reinforcement-learning safety

Related stories

FSA-GRPO: Teaching Auditory LLMs to Use Few-shot Demonstrations

Encoder-Side Neuron Identification and Amplification for Acoustic Perception in Large Audio-Language Models

Unified Audio Intelligence Without Regressing on Text Intelligence

VoxZip: Semantic-Anchored Temporal KV Cache Compression for Long-Context Audio Inference

X$^3$-OPD: Distilling Reasoning into Large Audio-Language Models via On-Policy Alignment

GenTSE: Enhancing Target Speaker Extraction via a Coarse-to-Fine Generative Language Model