
Tuna Meral
@tunahansalih
CS PhD @Virginia_Tech, Vision GenAI
Was working on making sense of visuals,
Now working on visuals making sense
Upcoming @amazon, ex @Adobe intern
🇹🇷/🇺🇸
ID: 124761807
https://tunahansalih.github.io/ 20-03-2010 13:37:41
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ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features Oral presentation Alec Helbling Tuna Meral (VT) Ben Hoover Pinar Yanardag (VT) Duen Horng Chau arxiv.org/abs/2502.04320 TL;DR: Saliency without supervision: unlocks hidden concept awareness in DiTs

NeurIPS Conference, why take the option to provide figures in the rebuttals away from the authors during the rebuttal period? Grounding the discussion in hard evidential data (like plots) makes resolving disagreements much easier for both the authors and the reviewers. Left: NeurIPS


The best part of the new NeurIPS Conference rebuttal policy is getting to write a 500-word essay describing what my image generation output for "a Cthulhu-themed waterpark" looks like for Reviewer 2 instead of just... showing them the picture. 😅




Ph.D. student Tuna Meral's (Tuna Meral) home base for summer was Amazon Science AGI Foundations, San Francisco. As applied scientist intern on video generation team, he helped develop autoregressive models for creating both images & video. His advisor The Sanghani Center at Virginia Tech: Pinar Yanardag


