123 citations · 167 across the 10 of their papers we have counts for
11 papers
CAVE: Detecting and Explaining Commonsense Anomalies in Visual Environments
Rishika Bhagwatkar, Syrielle Montariol, Angelika Romanou +3
Humans can naturally identify, reason about, and explain anomalies in their environment. In computer vision, this long-standing challenge remains limited to industrial defects or u…
Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
Project Apertus, Alejandro Hernández-Cano, Alexander Hägele +100
We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingu…
Retrieval-Based Interleaved Visual Chain-of-Thought in Real-World Driving Scenarios
Charles Corbière, Simon Roburin, Syrielle Montariol +2
While chain-of-thought (CoT) prompting improves reasoning in large language models, its effectiveness in vision-language models (VLMs) remains limited due to over-reliance on textu…
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
Angelika Romanou, Negar Foroutan, Anna Sotnikova +56
The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…
MEDITRON-70B: Scaling Medical Pretraining for Large Language Models
Zeming Chen, Alejandro Hernández Cano, Angelika Romanou +17
Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made to harness and improve LLMs' medical knowledge and reasoning…
CRAB: Assessing the Strength of Causal Relationships Between Real-world Events
Angelika Romanou, Syrielle Montariol, Debjit Paul +3
Understanding narratives requires reasoning about the cause-and-effect relationships between events mentioned in the text. While existing foundation models yield impressive results…
Multilingual Auxiliary Tasks Training: Bridging the Gap between Languages for Zero-Shot Transfer of Hate Speech Detection Models
Syrielle Montariol, Arij Riabi, Djamé Seddah
Zero-shot cross-lingual transfer learning has been shown to be highly challenging for tasks involving a lot of linguistic specificities or when a cultural gap is present between la…
Capturing Evolution in Word Usage: Just Add More Clusters?
Matej Martinc, Syrielle Montariol, Elaine Zosa +1
The way the words are used evolves through time, mirroring cultural or technological evolution of society. Semantic change detection is the task of detecting and analysing word evo…
Empirical Study of Diachronic Word Embeddings for Scarce Data
Syrielle Montariol, Alexandre Allauzen
Word meaning change can be inferred from drifts of time-varying word embeddings. However, temporal data may be too sparse to build robust word embeddings and to discriminate signif…
Learning dynamic word embeddings with drift regularisation
Syrielle Montariol, Alexandre Allauzen
Word usage, meaning and connotation change throughout time. Diachronic word embeddings are used to grasp these changes in an unsupervised way. In this paper, we use variants of the…
Exploring sentence informativeness
Syrielle Montariol, Aina Garí Soler, Alexandre Allauzen
This study is a preliminary exploration of the concept of informativeness -how much information a sentence gives about a word it contains- and its potential benefits to building qu…