4 papers
Adaptive Chunking: Optimizing Chunking-Method Selection for RAG
Paulo Roberto de Moura Júnior, Jean Lelong, Annabelle Blangero
The effectiveness of Retrieval-Augmented Generation (RAG) is highly dependent on how documents are chunked, that is, segmented into smaller units for indexing and retrieval. Yet, c…
Towards Faithful Multimodal Concept Bottleneck Models
Pierre Moreau, Emeline Pineau Ferrand, Yann Choho +3
Concept Bottleneck Models (CBMs) are interpretable models that route predictions through a layer of human-interpretable concepts. While widely studied in vision and, more recently,…
In-Distribution Steering: Balancing Control and Coherence in Language Model Generation
Arthur Vogels, Benjamin Wong, Yann Choho +2
Activation steering methods control large language model (LLM) behavior by modifying internal activations at inference time. However, most existing activation steering methods rely…
Agentic RAG with Knowledge Graphs for Complex Multi-Hop Reasoning in Real-World Applications
Jean Lelong, Adnane Errazine, Annabelle Blangero
Conventional Retrieval-Augmented Generation (RAG) systems enhance Large Language Models (LLMs) but often fall short on complex queries, delivering limited, extractive answers and s…