1 citations · 2 across the 26 of their papers we have counts for
10 papers · 1 filter
Happiness as a Measure of Fairness
Georg Pichler, Marco Romanelli, Pablo Piantanida
In this paper, we propose a novel fairness framework grounded in the concept of happiness, a measure of the utility each group gains fromdecisionoutcomes. Bycapturingfairness throu…
QueStER: Query Specification for Generative keyword-based Retrieval
Arthur Satouf, Yuxuan Zong, Habiboulaye Amadou-Boubacar +2
Generative retrieval (GR) differs from the traditional index-then-retrieve pipeline by storing relevance in model parameters and generating retrieval cues directly from the query,…
Learning Task-Agnostic Representations through Multi-Teacher Distillation
Philippe Formont, Maxime Darrin, Banafsheh Karimian +5
Casting complex inputs into tractable representations is a critical step across various fields. Diverse embedding models emerge from differences in architectures, loss functions, i…
How Sampling Affects the Detectability of Machine-written texts: A Comprehensive Study
Matthieu Dubois, François Yvon, Pablo Piantanida
As texts generated by Large Language Models (LLMs) are ever more common and often indistinguishable from human-written content, research on automatic text detection has attracted g…
Collaborative Rational Speech Act: Pragmatic Reasoning for Multi-Turn Dialog
Lautaro Estienne, Gabriel Ben Zenou, Nona Naderi +2
As AI systems take on collaborative roles, they must reason about shared goals and beliefs-not just generate fluent language. The Rational Speech Act (RSA) framework offers a princ…
THUNDER: Tile-level Histopathology image UNDERstanding benchmark
Pierre Marza, Leo Fillioux, Sofiène Boutaj +6
Progress in a research field can be hard to assess, in particular when many concurrent methods are proposed in a short period of time. This is the case in digital pathology, where…
: A Rhetorical-Strategy-Aware Rational Speech Act Framework for Figurative Language Understanding
Cesare Spinoso-Di Piano, David Austin, Pablo Piantanida +1
Figurative language (e.g., irony, hyperbole, understatement) is ubiquitous in human communication, resulting in utterances where the literal and the intended meanings do not match.…
Rational Retrieval Acts: Leveraging Pragmatic Reasoning to Improve Sparse Retrieval
Arthur Satouf, Gabriel Ben Zenou, Benjamin Piwowarski +2
Current sparse neural information retrieval (IR) methods, and to a lesser extent more traditional models such as BM25, do not take into account the document collection and the comp…
Statistical Deficiency for Task Inclusion Estimation
Loïc Fosse, Frédéric Béchet, Benoît Favre +5
Tasks are central in machine learning, as they are the most natural objects to assess the capabilities of current models. The trend is to build general models able to address any t…
BayesAdapter: enhanced uncertainty estimation in CLIP few-shot adaptation
Pablo Morales-Álvarez, Stergios Christodoulidis, Maria Vakalopoulou +2
The emergence of large pre-trained vision-language models (VLMs) represents a paradigm shift in machine learning, with unprecedented results in a broad span of visual recognition t…