2 papers
cs.LG2026
Learning Retrieval Models with Sparse Autoencoders
Thibault Formal, Maxime Louis, Hervé Dejean +1
Sparse autoencoders (SAEs) provide a powerful mechanism for decomposing the dense representations produced by Large Language Models (LLMs) into interpretable latent features. We po…
cs.IR2024
Two-Step SPLADE: Simple, Efficient and Effective Approximation of SPLADE
Carlos Lassance, Hervé Dejean, Stéphane Clinchant +1
Learned sparse models such as SPLADE have successfully shown how to incorporate the benefits of state-of-the-art neural information retrieval models into the classical inverted ind…