50 citations · 57 across the 6 of their papers we have counts for
6 papers
A Table Is Worth 64 Tokens: Pixel-level Compression for Multi-Table Document Question Answering
Iñigo Alonso, Mirella Lapata
Answering questions over real-world documents requires processing long inputs that interleave text with tables. Optical context compression, which represents context as images, pro…
TABLET: A Large-Scale Dataset for Robust Visual Table Understanding
Iñigo Alonso, Imanol Miranda, Eneko Agirre +1
While table understanding increasingly relies on pixel-only settings, current benchmarks predominantly use synthetic renderings that lack the complexity and visual diversity of rea…
Vision-Language Models Struggle to Align Entities across Modalities
Iñigo Alonso, Gorka Azkune, Ander Salaberria +2
Cross-modal entity linking refers to the ability to align entities and their attributes across different modalities. While cross-modal entity linking is a fundamental skill needed…
MedExpQA: Multilingual Benchmarking of Large Language Models for Medical Question Answering
Iñigo Alonso, Maite Oronoz, Rodrigo Agerri
Large Language Models (LLMs) have the potential of facilitating the development of Artificial Intelligence technology to assist medical experts for interactive decision support, wh…
PixT3: Pixel-based Table-To-Text Generation
Iñigo Alonso, Eneko Agirre, Mirella Lapata
Table-to-text generation involves generating appropriate textual descriptions given structured tabular data. It has attracted increasing attention in recent years thanks to the pop…
Automatic Logical Forms improve fidelity in Table-to-Text generation
Iñigo Alonso, Eneko Agirre
Table-to-text systems generate natural language statements from structured data like tables. While end-to-end techniques suffer from low factual correctness (fidelity), a previous…