activity
20242026
collaborators

14 papers

cs.CL2026

When Trivia Is Not Trivial: Everyday Knowledge Failures in Multilingual LLMs

Anna Mosolova, Djamé Seddah

Quiz rooms, trivia nights, and quiz shows challenge human knowledge across a wide range of topics, from canonical facts to everyday culture. In this paper, we examine whether large…

cs.CL2026

When Tables Go Crazy: Evaluating Multimodal Models on French Financial Documents

Virginie Mouilleron, Théo Lasnier, Anna Mosolova +1

Vision-language models (VLMs) perform well on many document understanding tasks, yet their reliability in specialized, non-English domains remains underexplored. This gap is especi…

cs.CL2026

Multi-Hop Knowledge Composition is Bound by Pretraining Exposure

Yannis Karmim, Luis Marti, Djamé Seddah +1

Large Language Models fail at implicit multi-hop reasoning: a model answers "When was born?" and "Who is 's closest friend?" correctly but fails on "When was 's closest f…

cs.CL2026

Backdoor Unlearning Generalization: A Path Toward the Removal of Unknown Triggers in LLMs

Lisa Bouger, Théo Lasnier, Philippe Loubet Moundi +2

Backdoor attacks in Large Language Models (LLMs) are a growing security concern, where models can generate adversary-chosen content. Existing defenses target backdoors one at a tim…

cs.CL2026

Translation Heads: Disentangling meaning from language in LLM-based machine translation

Théo Lasnier, Armel Zebaze, Djamé Seddah +2

Mechanistic Interpretability (MI) seeks to explain how neural networks implement their capabilities, but the scale of Large Language Models (LLMs) has limited prior MI work in Mach…

cs.CL2026

Rethinking the Multilingual Reasoning Gap with Layer Swap

Maxence Lasbordes, Amélie Chatelain, Djamé Seddah

Recent reasoning Large Language Models produce a chain-of-thought (CoT) predominantly in English, even when prompted in non-English languages. Prior work suggests that forcing the…