AI ↔ Cognition

What language models reveal about human reasoning and development.

AI ↔ Cognition

Large language models double as computational subjects. This theme captures how BabyLM, cognitive batteries, and psycholinguistic analyses expose where models follow-or diverge from-human developmental trajectories.

  • Teaching Language Models to Grow Up - Developmentally staged corpora and cognitive test batteries.
  • How Well Do Deep Learning Models Capture Human Concepts? - Typicality effects and concept representations.

Highlights

  1. Developmental Alignment
    • Age-restricted corpora (BabyLM challenge) for staged learning
    • Curriculum experiments that mimic child-directed input
  2. Psych-inspired Evaluation Batteries
    • Garden-path recovery, numerical magnitude, typicality gradients
    • Linking hypotheses mapping behavioral signatures to model internals
  3. Theory ↔ Practice Loop
    • Insights that inform safer training objectives
    • Cognitive science collaborations that keep the benchmarks grounded

Get Involved

  • Submit to the next BabyLM workshop
  • Run your model through the cognitive battery and share results
  • Co-design new linking hypotheses bridging psych data and LLM latents

Reach out if you want to pair up-this line thrives on interdisciplinary partnerships.