VLMs show partial alignment with children's performance on six cognitive tasks, with stronger models matching better at task and item levels but struggling on matrix reasoning and mental rotation.
Sparks, Zi Yin, Virginia A
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Current VLMs depend on tightly aligned curated data and cannot exploit the weakly-aligned egocentric video signals that dominate naturalistic infant input.
A zero-shot visual world model trained on one child's experience achieves broad competence on physical understanding benchmarks while matching developmental behavioral patterns.
citing papers explorer
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LEVANTE-bench: Multi-Scale Comparison of VLMs to Children Using Cognitive Tasks (or, "Is Your VLM Smarter Than a 5th Grader?")
VLMs show partial alignment with children's performance on six cognitive tasks, with stronger models matching better at task and item levels but struggling on matrix reasoning and mental rotation.
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EgoBabyVLM: Benchmarking Cross-Modal Learning from Naturalistic Egocentric Video Data
Current VLMs depend on tightly aligned curated data and cannot exploit the weakly-aligned egocentric video signals that dominate naturalistic infant input.