9 citations · 12 across the 5 of their papers we have counts for
6 papers
The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes
Redacted by arXiv
This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd conte…
More Is Better: A MoE-Based Emotion Recognition Framework with Human Preference Alignment
Jun Xie, Yingjian Zhu, Feng Chen +9
In this paper, we present our solution for the semi-supervised learning track (MER-SEMI) in MER2025. We propose a comprehensive framework, grounded in the principle that "more is b…
CARES: Comprehensive Evaluation of Safety and Adversarial Robustness in Medical LLMs
Sijia Chen, Xiaomin Li, Mengxue Zhang +3
Large language models (LLMs) are increasingly deployed in medical contexts, raising critical concerns about safety, alignment, and susceptibility to adversarial manipulation. While…
Dynamic Depth Decoding: Faster Speculative Decoding for LLMs
Oscar Brown, Zhengjie Wang, Andrea Do +2
The acceleration of Large Language Models (LLMs) with speculative decoding provides a significant runtime improvement without any loss of accuracy. Currently, EAGLE-2 is the state-…
Using fine-tuning and min lookahead beam search to improve Whisper
Andrea Do, Oscar Brown, Zhengjie Wang +4
The performance of Whisper in low-resource languages is still far from perfect. In addition to a lack of training data on low-resource languages, we identify some limitations in th…
ZR-2021VG: Zero-Resource Speech Challenge, Visually-Grounded Language Modelling track, 2021 edition
Afra Alishahi, Grzegorz Chrupała, Alejandrina Cristia +5
We present the visually-grounded language modelling track that was introduced in the Zero-Resource Speech challenge, 2021 edition, 2nd round. We motivate the new track and discuss…