3 citations · 5 across the 9 of their papers we have counts for
10 papers
Scaling cross-situational word learning on children's naturalistic experiences
Michael C. Frank, Alvin W. M. Tan, Khai Loong Aw +9
How do children learn the meanings of the simple, concrete words that form a majority of their early vocabulary? Statistical information about many word meanings can be recovered f…
Which one is banana man? Evaluating vision-language models in multi-turn pragmatic interpretation
Alvin Wei Ming Tan, Ben Prystawski, Veronica Boyce
Flexible adaptation to context and shared pragmatic intuitions contribute to smooth human conversation. Iterated reference games---in which players repeatedly pick out novel refere…
LEVANTE-bench: Multi-Scale Comparison of VLMs to Children Using Cognitive Tasks (or, "Is Your VLM Smarter Than a 5th Grader?")
Alvin Wei Ming Tan, David Cardinal, Tania Lorido-Botran +3
Given the inherently multimodal nature of human experience, vision-language models (VLMs) hold substantial promise for modeling human cognition as it grows and develops with experi…
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…
Characterizing the visual representation of objects from the child's view
Jane Yang, Tarun Sepuri, Alvin Wei Ming Tan +3
Children acquire object category representations from their everyday experiences in the first few years of life. What do the inputs to this learning process look like? We analyzed…
Baby Scale: Investigating Models Trained on Individual Children's Language Input
Steven Y. Feng, Alvin W. M. Tan, Michael C. Frank
Modern language models (LMs) must be trained on many orders of magnitude more words of training data than human children receive before they begin to produce useful behavior. Asses…
Assessing the alignment between infants' visual and linguistic experience using multimodal language models
Alvin Wei Ming Tan, Jane Yang, Tarun Sepuri +6
Figuring out which objects or concepts words refer to is a central language learning challenge for young children. Most models of this process posit that children learn early objec…
Context informs pragmatic interpretation in vision-language models
Alvin Wei Ming Tan, Ben Prystawski, Veronica Boyce +1
Iterated reference games - in which players repeatedly pick out novel referents using language - present a test case for agents' ability to perform context-sensitive pragmatic reas…
The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiences
Bria Long, Robert Z. Sparks, Violet Xiang +9
Human children far exceed modern machine learning algorithms in their sample efficiency, achieving high performance in key domains with much less data than current models. This ''d…
DevBench: A multimodal developmental benchmark for language learning
Alvin Wei Ming Tan, Sunny Yu, Bria Long +5
How (dis)similar are the learning trajectories of vision-language models and children? Recent modeling work has attempted to understand the gap between models' and humans' data eff…