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Making Sense of Touch from the Child's View for Contrastive Learning

arXiv 2606.31943 ↗First posted 30 Jun 2026cs.LGcited by 0

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Abstract (arXiv)

Is the sense of touch a mechanism for human babies' learning of visual concepts? If so, can we quantify its importance, and to what extent do babies rely on their sense of touch for visual learning? To approach these questions in a principled way, we propose a structured coding system for baby-centric touch events, yielding a dataset of 264k two-second clips of touch events coded according to this system. Using this dataset, we pretrain developmentally grounded models that reveal promising insights into the nature of baby learning from touch.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 22 references that are in the map. First posted on arXiv 30 Jun 2026.

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6 of 22 references.

References · 6

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,322
  3. 2021VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Textcited by 429
  4. 2024The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiencescited by 17
  5. 2025BabyVLM: Data-Efficient Pretraining of VLMs Inspired by Infant Learningcited by 6
  6. 2025BabyVLM-V2: Toward Developmentally Grounded Pretraining and Benchmarking of Vision Foundation Modelscited by 4

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