Predicting Word Learning in Children from the Performance of Computer Vision Systems. - Sunayana Rane; Mira L. Nencheva; Zeyu Wang 004; Casey Lew-Williams; Olga Russakovsky; Tom Griffiths 001 (CogSci, 2023)

Getting aligned on representational alignment. - Ilia Sucholutsky; Lukas Muttenthaler; Adrian Weller; Andi Peng; Andreea Bobu; Been Kim; Bradley C. Love; Erin Grant; Jascha Achterberg; Joshua B. Tenenbaum; Katherine M. Collins; Katherine L. Hermann; et al. (CoRR, 2023)

Concept Alignment as a Prerequisite for Value Alignment. - Sunayana Rane; Mark K. Ho; Ilia Sucholutsky; Thomas L. Griffiths 001 (CoRR, 2023)

DOCCI: Descriptions of Connected and Contrasting Images. - Yasumasa Onoe; Sunayana Rane; Zachary Berger; Yonatan Bitton; Jaemin Cho 001; Roopal Garg; Alexander Ku; Zarana Parekh; Jordi Pont-Tuset; Garrett Tanzer; Su Wang 001; Jason Baldridge (ECCV (60), 2024)

Position: The Reasonable Person Standard for AI. - Sunayana Rane (ICML, 2024)

Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem. - Declan Campbell; Sunayana Rane; Tyler Giallanza; Nicolò De Sabbata; Kia Ghods; Amogh Joshi 004; Alexander Ku; Steven Frankland; Tom Griffiths 001; Jonathan D. Cohen 003; Taylor W. Webb (NeurIPS, 2024)

Concept Alignment. - Sunayana Rane; Polyphony J. Bruna; Ilia Sucholutsky; Christopher T. Kello; Thomas L. Griffiths 001 (CoRR, 2024)

The Reasonable Person Standard for AI. - Sunayana Rane (CoRR, 2024)

Convolutional Neural Networks Can (Meta-)Learn the Same-Different Relation. - Max Gupta; Sunayana Rane; R. Thomas McCoy; Thomas L. Griffiths 001 (CoRR, 2025)