1 citations · 1 across the 13 of their papers we have counts for
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Extreme Multi-label Completion for Semantic Document Labelling with Taxonomy-Aware Parallel Learning
Julien Audiffren, Christophe Broillet, Ljiljana Dolamic +1
In Extreme Multi Label Completion (XMLCo), the objective is to predict the missing labels of a collection of documents. Together with XML Classification, XMLCo is arguably one of t…
NMT-Obfuscator Attack: Ignore a sentence in translation with only one word
Sahar Sadrizadeh, César Descalzo, Ljiljana Dolamic +1
Neural Machine Translation systems are used in diverse applications due to their impressive performance. However, recent studies have shown that these systems are vulnerable to car…
Can the Variation of Model Weights be used as a Criterion for Self-Paced Multilingual NMT?
Àlex R. Atrio, Alexis Allemann, Ljiljana Dolamic +1
Many-to-one neural machine translation systems improve over one-to-one systems when training data is scarce. In this paper, we design and test a novel algorithm for selecting the l…
LLM Detectors Still Fall Short of Real World: Case of LLM-Generated Short News-Like Posts
Henrique Da Silva Gameiro, Andrei Kucharavy, Ljiljana Dolamic
With the emergence of widely available powerful LLMs, disinformation generated by large Language Models (LLMs) has become a major concern. Historically, LLM detectors have been tou…
Sparse vs Contiguous Adversarial Pixel Perturbations in Multimodal Models: An Empirical Analysis
Cristian-Alexandru Botocan, Raphael Meier, Ljiljana Dolamic
Assessing the robustness of multimodal models against adversarial examples is an important aspect for the safety of its users. We craft L0-norm perturbation attacks on the preproce…
Implicit Probabilistic Reasoning Does Not Reflect Explicit Answers in Large Language Models
Manuel Mondal, Ljiljana Dolamic, Gérôme Bovet +2
The handling of probabilities in the form of uncertainty or partial information is an essential task for LLMs in many settings and applications. A common approach to evaluate an LL…