18 citations · 35 across the 7 of their papers we have counts for
11 papers
Faithful Chart Summarization with ChaTS-Pi
Syrine Krichene, Francesco Piccinno, Fangyu Liu +1
Chart-to-summary generation can help explore data, communicate insights, and help the visually impaired people. Multi-modal generative models have been used to produce fluent summa…
DePlot: One-shot visual language reasoning by plot-to-table translation
Fangyu Liu, Julian Martin Eisenschlos, Francesco Piccinno +7
Visual language such as charts and plots is ubiquitous in the human world. Comprehending plots and charts requires strong reasoning skills. Prior state-of-the-art (SOTA) models req…
MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering
Fangyu Liu, Francesco Piccinno, Syrine Krichene +6
Visual language data such as plots, charts, and infographics are ubiquitous in the human world. However, state-of-the-art vision-language models do not perform well on these data.…
Table-To-Text generation and pre-training with TabT5
Ewa Andrejczuk, Julian Martin Eisenschlos, Francesco Piccinno +2
Encoder-only transformer models have been successfully applied to different table understanding tasks, as in TAPAS (Herzig et al., 2020). A major limitation of these architectures…
DoT: An efficient Double Transformer for NLP tasks with tables
Syrine Krichene, Thomas Müller, Julian Martin Eisenschlos
Transformer-based approaches have been successfully used to obtain state-of-the-art accuracy on natural language processing (NLP) tasks with semi-structured tables. These model arc…
TAPAS at SemEval-2021 Task 9: Reasoning over tables with intermediate pre-training
Thomas Müller, Julian Martin Eisenschlos, Syrine Krichene
We present the TAPAS contribution to the Shared Task on Statement Verification and Evidence Finding with Tables (SemEval 2021 Task 9, Wang et al. (2021)). SEM TAB FACT Task A is a…
Open Domain Question Answering over Tables via Dense Retrieval
Jonathan Herzig, Thomas Müller, Syrine Krichene +1
Recent advances in open-domain QA have led to strong models based on dense retrieval, but only focused on retrieving textual passages. In this work, we tackle open-domain QA over t…
Understanding tables with intermediate pre-training
Julian Martin Eisenschlos, Syrine Krichene, Thomas Müller
Table entailment, the binary classification task of finding if a sentence is supported or refuted by the content of a table, requires parsing language and table structure as well a…
Embedding models for recommendation under contextual constraints
Syrine Krichene, Mike Gartrell, Clement Calauzenes
Embedding models, which learn latent representations of users and items based on user-item interaction patterns, are a key component of recommendation systems. In many applications…
Learning Nonsymmetric Determinantal Point Processes
Mike Gartrell, Victor-Emmanuel Brunel, Elvis Dohmatob +1
Determinantal point processes (DPPs) have attracted substantial attention as an elegant probabilistic model that captures the balance between quality and diversity within sets. DPP…
Improving Evolutionary Strategies with Generative Neural Networks
Louis Faury, Clement Calauzenes, Olivier Fercoq +1
Evolutionary Strategies (ES) are a popular family of black-box zeroth-order optimization algorithms which rely on search distributions to efficiently optimize a large variety of ob…