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20192026
most citedImproved Large-margin Softmax Loss for Speaker Diarisation

10 citations · 19 across the 15 of their papers we have counts for

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9 papers · 1 filter

cs.CL2026★ 3 cited

Gemma 4 Technical Report

Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320

We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemm…

cs.CL2024★ 1 cited

Cross-Lingual Transfer Learning for Speech Translation

Rao Ma, Mengjie Qian, Yassir Fathullah +3

There has been increasing interest in building multilingual foundation models for NLP and speech research. This paper examines how to expand the speech translation capability of th…

cs.CL2024

Efficient LLM Comparative Assessment: a Product of Experts Framework for Pairwise Comparisons

Adian Liusie, Vatsal Raina, Yassir Fathullah +1

LLM-as-a-judge approaches are a practical and effective way of assessing a range of text tasks. However, when using pairwise comparisons to rank a set of candidates, the computatio…

cs.CL2024

Efficient Sample-Specific Encoder Perturbations

Yassir Fathullah, Mark J. F. Gales

Encoder-decoder foundation models have displayed state-of-the-art performance on a range of autoregressive sequence tasks. This paper proposes a simple and lightweight modification…

cs.CL2024

Teacher-Student Training for Debiasing: General Permutation Debiasing for Large Language Models

Adian Liusie, Yassir Fathullah, Mark J. F. Gales

Large Language Models (LLMs) have demonstrated impressive zero-shot capabilities and versatility in NLP tasks, however they sometimes fail to maintain crucial invariances for speci…

cs.CL2023

AudioChatLlama: Towards General-Purpose Speech Abilities for LLMs

Yassir Fathullah, Chunyang Wu, Egor Lakomkin +7

In this work, we extend the instruction-tuned Llama-2 model with end-to-end general-purpose speech processing and reasoning abilities while maintaining the wide range of original L…

cs.CL2023

TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-device ASR Models

Yuan Shangguan, Haichuan Yang, Danni Li +11

Automatic Speech Recognition (ASR) models need to be optimized for specific hardware before they can be deployed on devices. This can be done by tuning the model's hyperparameters…

cs.CL2023

CUED at ProbSum 2023: Hierarchical Ensemble of Summarization Models

Potsawee Manakul, Yassir Fathullah, Adian Liusie +3

In this paper, we consider the challenge of summarizing patients' medical progress notes in a limited data setting. For the Problem List Summarization (shared task 1A) at the BioNL…

cs.CL2020

Ensemble Distillation Approaches for Grammatical Error Correction

Yassir Fathullah, Mark Gales, Andrey Malinin

Ensemble approaches are commonly used techniques to improving a system by combining multiple model predictions. Additionally these schemes allow the uncertainty, as well as the sou…