3 papers
cs.LG2026
EgoBabyVLM: Benchmarking Cross-Modal Learning from Naturalistic Egocentric Video Data
Dongyan Lin, Phillip Rust, Angel Villar Corrales +19
Children acquire language grounding with remarkable robustness from limited visuo-linguistic input in ways that surpass today's best large multimodal models. Recent research sugges…
cs.CL2026
SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation
Mahi Luthra, Jiayi Shen, Maxime Poli +14
Human infants, with only a few hundred hours of speech exposure, acquire basic units of new languages, highlighting a striking efficiency gap compared to the data-hungry self-super…
cs.CL2025
SpidR: Learning Fast and Stable Linguistic Units for Spoken Language Models Without Supervision
Maxime Poli, Mahi Luthra, Youssef Benchekroun +8
The parallel advances in language modeling and speech representation learning have raised the prospect of learning language directly from speech without textual intermediates. This…