Syrielle Mathilde Marie Montariol

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Understanding narratives requires reasoning about the cause-and-effect relationships between events mentioned in the text. While existing foundation models yield impressive results in many NLP tasks requiring reasoning, it is unclear whether they understan ...

Instruction-tuning is a widely adopted finetuning method that enables large language models (LLMs) to generate output that more closely resembles human responses. However, no studies have shown that instruction-tuning actually teaches LLMs to process langu ...

Cross-view geo-localization aims at localizing a ground-level query image by matching it to its corresponding geo-referenced aerial view. In real-world scenarios, the task requires accommodating diverse ground images captured by users with varying orientat ...

Asking questions about visual environments is a crucial way for intelligent agents to understand rich multi-faceted scenes, raising the importance of Visual Question Generation (VQG) systems. Apart from being grounded to the image, existing VQG systems can ...

Recently, generalist Vision Language Models (VLMs) have shown exceptional progress in tasks previously dominated by specialized computer vision models. This becomes more prevalent when visual grounding capabilities, such as the ability to reason over input ...

Recent efforts in natural language processing (NLP) commonsense reasoning research have yielded a considerable number of new datasets and benchmarks. However, most of these datasets formulate commonsense reasoning challenges in artificial scenarios that ar ...

Weight-based model editing methods update the parametric knowledge of language models post-training. However, these methods can unintentionally alter unrelated parametric knowledge representations, potentially increasing the risk of harm. In this work, we ...

Current course recommender systems primarily leverage learner-course interactions, course content, learner preferences, and supplementary course details like instructor, institution, ratings, and reviews, to make their recommendation. However, these system ...

Syrielle Mathilde Marie Montariol

Chattez avec Graph Search

CRAB: Assessing the Strength of Causal Relationships Between Real-World Events

Instruction-tuned LLMs with World Knowledge are More Aligned to the Human Brain

ConGeo: Robust Cross-View Geo-Localization Across Ground View Variations

ConVQG: Contrastive Visual Question Generation with Multimodal Guidance

Training Visual Language Models with Object Detection: Grounded Change Descriptions in Satellite Images

CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks

“Flex Tape Can't Fix That”: Bias and Misinformation in Edited Language Models

Course Recommender Systems Need to Consider the Job Market