most citedSample-efficient Integration of New Modalities into Large Language Models

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

collaborators

5 papers

cs.LG2025

Learning with the -adics

André F. T. Martins

Existing machine learning frameworks operate over the field of real numbers () and learn representations in real (Euclidean or Hilbert) vector spaces (e.g., $\mathbb{R}…

cs.CL20251 cited

Sample-efficient Integration of New Modalities into Large Language Models

Osman Batur İnce, André F. T. Martins, Oisin Mac Aodha +1

Multimodal foundation models can process several modalities. However, since the space of possible modalities is large and evolving over time, training a model from scratch to encom…

cs.CL2025

Instituto de Telecomunicações at IWSLT 2025: Aligning Small-Scale Speech and Language Models for Speech-to-Text Learning

Giuseppe Attanasio, Sonal Sannigrahi, Ben Peters +1

This paper presents the IT-IST submission to the IWSLT 2025 Shared Task on Instruction Following Speech Processing. We submit results for the Short Track, i.e., speech recognition,…

cs.CL2025

From TOWER to SPIRE: Adding the Speech Modality to a Translation-Specialist LLM

Kshitij Ambilduke, Ben Peters, Sonal Sannigrahi +5

We introduce Spire, a speech-augmented language model (LM) capable of both translating and transcribing speech input from English into 10 other languages as well as translating tex…

cs.CL2025

AdaSplash: Adaptive Sparse Flash Attention

Nuno Gonçalves, Marcos Treviso, André F. T. Martins

The computational cost of softmax-based attention in transformers limits their applicability to long-context tasks. Adaptive sparsity, of which -entmax attention is an example,…