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20242026
most citedThe Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes

1 citations · 1 across the 3 of their papers we have counts for

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eess.AS2026

MELD: Mel-Spectrogram-Based Speech Language Modeling with Discrete Latent Variables

Sung-Lin Yeh, Wei Zhou, Gil Keren +6

Recent speech language models rely on encoders that are optimized separately from autoregressive models. Since these encoders are unaware of the downstream objectives, the extracte…

eess.AS2025

Frozen Large Language Models Can Perceive Paralinguistic Aspects of Speech

Wonjune Kang, Junteng Jia, Chunyang Wu +8

This work studies the capabilities of a large language model (LLM) to understand paralinguistic aspects of speech without fine-tuning its weights. We utilize an end-to-end system w…

eess.AS2024

CJST: CTC Compressor based Joint Speech and Text Training for Decoder-Only ASR

Wei Zhou, Junteng Jia, Leda Sari +2

CTC compressor can be an effective approach to integrate audio encoders to decoder-only models, which has gained growing interest for different speech applications. In this work, w…

eess.AS2024

M-BEST-RQ: A Multi-Channel Speech Foundation Model for Smart Glasses

Yufeng Yang, Desh Raj, Ju Lin +8

The growing popularity of multi-channel wearable devices, such as smart glasses, has led to a surge of applications such as targeted speech recognition and enhanced hearing. Howeve…

eess.AS2024

Faster Speech-LLaMA Inference with Multi-token Prediction

Desh Raj, Gil Keren, Junteng Jia +2

Large language models (LLMs) have become proficient at solving a wide variety of tasks, including those involving multi-modal inputs. In particular, instantiating an LLM (such as L…