In the last 48h:
- Jr researcher asked me wheter to use AI in making talks
- Saw two talks, with AI {slop, enhanced} slides
Collected my thoughts and wrote a post. Tl;dr: don't steal your own thinking, don't remove *you* from your talks. Also, give a &#@% about your talks.
A clearly hallucinated citation! NeurIPS 2026 decisions aren't out yet. But wait --- the hallucination is also present in the bibtex entries from openreview openreview.net/forum?id=fAj... and Google Scholar scholar.googleusercontent.com/scholar.bib?...
Recently we showed that the minimax optimal rate for multicalibration is T^{2/3}. But that doesn't mean you have to do that badly on all instances. We give an algorithm that can adapt to easy instances and get better rates while still being minimax optimal in the worst case.
arxiv.org/abs/2605.09273
Why do all LLMs predict 27 as their favorite number? There may be a principled explanation. Learn more at Agents in the Wild at #ICLR2026.
@ericeaton.bsky.social, me, @surbhigoel.bsky.social, @mkearnsphilly.bsky.social, @aaroth.bsky.social, @sikatasengupta.bsky.social, @optimistsinc.bsky.social
I'm giving this talk at the MIT CS theory seminar tomorrow. Stop by if you are around!
It might also be suggestive about why human research communities don't much overfit benchmark datasets despite reusing them for years. Joint work with Martin Bertran and @zstevenwu.bsky.social
I just learned about this closely related concurrent paper by Liu, Luo, and Ratliff that went up on arxiv yesterday: arxiv.org/abs/2605.11490 --- it also looks very interesting, check it out!