373 citations · 841 across the 71 of their papers we have counts for
77 papers
Muse Glimmer 30B: An On-Device Agentic Model
Arash Ebrahim Abtahizadeh, Muna Aghamelu, Adil Ahmed +327
We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware. Muse Glimmer…
OmnilingualGAIA2: Evaluating the Multilingual Gap in Frontier AI Agents
Andrea Caciolai, Pere-Lluís Huguet Cabot, Chierh Cheng +11
Agentic benchmarks aim to measure how well AI agents plan, search, execute, and recover within realistic multi-tool environments, but they are almost exclusively in English. As AI…
Omnilingual SONAR: Cross-Lingual and Cross-Modal Sentence Embeddings Bridging Massively Multilingual Text and Speech
Omnilingual SONAR Team, João Maria Janeiro, Pere-Lluís Huguet Cabot +17
Cross-lingual sentence encoders typically cover only a few hundred languages and often trade downstream quality for stronger alignment, limiting their adoption. We introduce OmniSO…
Omnilingual MT: Machine Translation for 1,600 Languages
Omnilingual MT Team, Belen Alastruey, Niyati Bafna +29
High-quality machine translation (MT) can scale to hundreds of languages, setting a high bar for multilingual systems. However, compared to the world's 7,000 languages, current sys…
Translate, then Detect: Leveraging Machine Translation for Cross-Lingual Toxicity Classification
Samuel J. Bell, Eduardo Sánchez, David Dale +3
Multilingual toxicity detection remains a significant challenge due to the scarcity of training data and resources for many languages. While prior work has leveraged the translate-…
Interference Matrix: Quantifying Cross-Lingual Interference in Transformer Encoders
Belen Alastruey, João Maria Janeiro, Alexandre Allauzen +3
In this paper, we present a comprehensive study of language interference in encoder-only Transformer models across 83 languages. We construct an interference matrix by training and…
Improving Language and Modality Transfer in Translation by Character-level Modeling
Ioannis Tsiamas, David Dale, Marta R. Costa-jussà
Current translation systems, despite being highly multilingual, cover only 5% of the world's languages. Expanding language coverage to the long-tail of low-resource languages requi…
BOUQuET: dataset, Benchmark and Open initiative for Universal Quality Evaluation in Translation
The Omnilingual MT Team, Pierre Andrews, Mikel Artetxe +14
BOUQuET is a multi-way, multicentric and multi-register/domain dataset and benchmark, and a broader collaborative initiative. This dataset is handcrafted in 8 non-English languages…
2M-BELEBELE: Highly Multilingual Speech and American Sign Language Comprehension Dataset
Marta R. Costa-jussà, Bokai Yu, Pierre Andrews +7
We introduce the first highly multilingual speech and American Sign Language (ASL) comprehension dataset by extending BELEBELE. Our dataset covers 74 spoken languages at the inters…
Large Concept Models: Language Modeling in a Sentence Representation Space
LCM team, Loïc Barrault, Paul-Ambroise Duquenne +18
LLMs have revolutionized the field of artificial intelligence and have emerged as the de-facto tool for many tasks. The current established technology of LLMs is to process input a…
Y-NQ: English-Yorùbá Evaluation dataset for Open-Book Reading Comprehension and Text Generation
Marta R. Costa-jussà, Joy Chen, Ifeoluwanimi Adebara +3
The purpose of this work is to share an English-Yorùbá evaluation dataset for open-book reading comprehension and text generation to assess the performance of models both in a high…
LCFO: Long Context and Long Form Output Dataset and Benchmarking
Marta R. Costa-jussà, Pierre Andrews, Mariano Coria Meglioli +10
This paper presents the Long Context and Form Output (LCFO) benchmark, a novel evaluation framework for assessing gradual summarization and summary expansion capabilities across di…
On the Role of Speech Data in Reducing Toxicity Detection Bias
Samuel J. Bell, Mariano Coria Meglioli, Megan Richards +6
Text toxicity detection systems exhibit significant biases, producing disproportionate rates of false positives on samples mentioning demographic groups. But what about toxicity de…
Unveiling the Role of Pretraining in Direct Speech Translation
Belen Alastruey, Gerard I. Gállego, Marta R. Costa-jussà
Direct speech-to-text translation systems encounter an important drawback in data scarcity. A common solution consists on pretraining the encoder on automatic speech recognition, h…
Linguini: A benchmark for language-agnostic linguistic reasoning
Eduardo Sánchez, Belen Alastruey, Christophe Ropers +3
We propose a new benchmark to measure a language model's linguistic reasoning skills without relying on pre-existing language-specific knowledge. The test covers 894 questions grou…
FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data
Haoran Sun, Renren Jin, Shaoyang Xu +10
Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…
Towards Massive Multilingual Holistic Bias
Xiaoqing Ellen Tan, Prangthip Hansanti, Carleigh Wood +3
In the current landscape of automatic language generation, there is a need to understand, evaluate, and mitigate demographic biases as existing models are becoming increasingly mul…
A Primer on the Inner Workings of Transformer-based Language Models
Javier Ferrando, Gabriele Sarti, Arianna Bisazza +1
The rapid progress of research aimed at interpreting the inner workings of advanced language models has highlighted a need for contextualizing the insights gained from years of wor…
Pushing the Limits of Zero-shot End-to-End Speech Translation
Ioannis Tsiamas, Gerard I. Gállego, José A. R. Fonollosa +1
Data scarcity and the modality gap between the speech and text modalities are two major obstacles of end-to-end Speech Translation (ST) systems, thus hindering their performance. P…
Spirit LM: Interleaved Spoken and Written Language Model
Tu Anh Nguyen, Benjamin Muller, Bokai Yu +13
We introduce Spirit LM, a foundation multimodal language model that freely mixes text and speech. Our model is based on a 7B pretrained text language model that we extend to the sp…
Towards Red Teaming in Multimodal and Multilingual Translation
Christophe Ropers, David Dale, Prangthip Hansanti +9
Assessing performance in Natural Language Processing is becoming increasingly complex. One particular challenge is the potential for evaluation datasets to overlap with training da…
MuTox: Universal MUltilingual Audio-based TOXicity Dataset and Zero-shot Detector
Marta R. Costa-jussà, Mariano Coria Meglioli, Pierre Andrews +6
Research in toxicity detection in natural language processing for the speech modality (audio-based) is quite limited, particularly for languages other than English. To address thes…
Seamless: Multilingual Expressive and Streaming Speech Translation
Seamless Communication, Loïc Barrault, Yu-An Chung +62
Large-scale automatic speech translation systems today lack key features that help machine-mediated communication feel seamless when compared to human-to-human dialogue. In this wo…
Added Toxicity Mitigation at Inference Time for Multimodal and Massively Multilingual Translation
Marta R. Costa-jussà, David Dale, Maha Elbayad +1
Added toxicity in the context of translation refers to the fact of producing a translation output with more toxicity than there exists in the input. In this paper, we present MinTo…