Who's Who of AI

Clément Canonne

404 trust researcher @ccanonne.github.io · 7,103 followers

AI research

Why they matter

Researcher with public evidence across AI research.

AI signals: 3
Sources: 2
Discusiones: 14
Latest signal: 10d ago

View every signal from Clément Canonne →

Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.

What they're sharing

Articles & links

A list of principles put forth by mathematicians, for mathematicians and other researchers, regarding the use of AI in research. "Number #9 will surprise you!" leidendeclaration.ai

Leiden Declaration on Artificial Intelligence and Mathematics leidendeclaration.ai

AI Weekly's analysis →

The Leiden Declaration, released June 2, 2026, warns AI threatens proof integrity, attribution, and peer review in mathematics.
Over 2,654 signatories including Fields Medal winner Terence Tao have endorsed the community-initiated declaration.
The International Mathematical Union backs the declaration, which makes separate recommendations to researchers, publishers, policymakers, and AI developers.

Read full analysis →

View on Bluesky · ♥ 26 ↻ 11 ↩ 0 · 14 from the directory shared this · 56d ago

Take some time (very little) to weigh on this: "Now Is the Time to Give LLMs Access to the ACM Digital Library" docs.google.com/forms/d/e/1F... (not that I want to influence anyone, but my own position is along the lines of "hell no.")

Now is the Time to Give LLMS Access to the ACM Digital Library Why ACM Believes the benefits outweigh the risks in opening up the ACM Digital Library to large language models docs.google.com

View on Bluesky · ♥ 10 ↻ 2 ↩ 3 · 3 from the directory shared this · 11d ago

Our paper on Entropy Equivalence Testing was just accepted to #RANDOM2026. Congratulations to Joy (Qiping) Yang and Yash Pote, who led the charge! arxiv.org/abs/2605.23225

[2605.23225] Entropy Equivalence Testing arxiv.org

AI Weekly's analysis →

Entropy equivalence testing needs significantly fewer samples than standard closeness testing for distributions.
The paper delivers the first non-trivial closeness testing algorithm for low-degree Bayesian networks.
Matching lower bounds establish near-optimality, revealing how hard the relaxed problem is in principle.

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View on Bluesky · ♥ 14 ↻ 1 ↩ 1 · 2 from the directory shared this · 33d ago

↻ Clément Canonne reposted

@dppapers.bsky.social

Near-Optimal Pure Machine Unlearning for Smooth Strongly Convex Losses Matthew Regehr, Gautam Kamath, Andrew Lowy http://arxiv.org/abs/2606.01527

Near-Optimal Pure Machine Unlearning for Smooth Strongly Convex Losses arxiv.org View on Bluesky →

↻ Clément Canonne reposted

@arxiv-cs-ds.bsky.social

Pan Peng, Yuyang Wang, Joy Qiping Yang, Yichun Yang An Exponential Lower Bound for Spectral Density Estimation on Unweighted Graphs https://arxiv.org/abs/2606.28188

An Exponential Lower Bound for Spectral Density Estimation on Unweighted Graphs arxiv.org View on Bluesky →

↻ Clément Canonne reposted

@dppapers.bsky.social

Optimal Rates for Differentially Private Hypothesis Testing with E-values Ben Jacobsen, Tomas Gonzales, Gavin Brown, Kassem Fawaz, Aaditya Ramdas http://arxiv.org/abs/2605.28952

Optimal Rates for Differentially Private Hypothesis Testing with E-values arxiv.org View on Bluesky →

New preprint online: on multiple trade-offs b/w communication, sample, and randomness complexities for the fundamental task of Gaussian mean testing in a distributed setting. Led by the brilliant Nimitt (undergrad at IIT Gandhinagar) during a remote internship last year! 📝 arx…

Distributed Gaussian Mean Testing under Communication Constraints: messages, samples, and coins arxiv.org

View on Bluesky · ♥ 13 ↻ 1 ↩ 0 · 60d ago

Good blog post by Suresh Venkatasubramanian (@geomblog.bsky.social) on the latest installment of the Spectacle regarding Anthropic and the US government. He brings the popcorn, but the receipts and analysis, too. blog.geomblog.org/2026/06/the-...

blog.geomblog.org

View on Bluesky · ♥ 10 ↻ 1 ↩ 0 · 3 from the directory shared this · 45d ago

Boaz is incredibly smart! Many are! Do they not realize that "I'm happily building a thing I genuinely believe can be compared to a planetary-scale catastrophe,* I suggest you make peace with it" is NOT great PR? (*Regardless of whether you/I believe it) windowsontheory.org/20…

AI is a Meteor. Don’t be a Dinosaur. windowsontheory.org

View on Bluesky · ♥ 18 ↻ 2 ↩ 5 · 2 from the directory shared this · 59d ago

↻ Clément Canonne reposted

@taylorjsmith.bsky.social

1961: CACM publishes Tony Hoare's quicksort algorithm. 2026: CACM publishes a self-promo article by some random guy who's pitting different LLMs against each other to pump unmitigated slop into a GitHub repo. Is this what my membership money's going toward, @acm.org?

cacm.acm.org View on Bluesky →

Their own posts

Recent commentary

The OpenAI breakthrough on the unit distance problem seems genuinely impressive to my semi-layman eye. (It is!) One possible takeaway, though, is that if you throw an incredible amount of money and resources at focused research, there WILL be impressive progress. I wish we tried that, too.

View on Bluesky · ♥ 41 ↻ 6 ↩ 1 · 69d ago

I uploaded a picture of a random root vegetable and asked ChatGPT to identify it. It told me it was a stochastic carrot.

View on Bluesky · ♥ 38 ↻ 2 ↩ 1 · 55d ago

"AI will replace U, they said" "Nothing yoai can do aboait it. It's the faitaire."

View on Bluesky · ♥ 17 ↻ 2 ↩ 3 · 72d ago

The Pope taking such a strong stance on AI feels rather unorthodox

View on Bluesky · ♥ 16 ↻ 1 ↩ 2 · 64d ago

Number of times the Jacobian Conjecture has been proven: Humans: 0 AI: 0 From what I can see it's a tie, nothing to worry about

View on Bluesky · ♥ 16 ↻ 0 ↩ 2 · 7d ago

I don't know what's happening with Google Scholar,* but lately I have been receiving a large number of absurd Google Scholar Alerts for papers anything from one to 15 years old. Is that widespread? *My fear is they offloaded GScholar to AI agents, and it's on a steady way to becoming unusable.

View on Bluesky · ♥ 10 ↻ 0 ↩ 3 · 45d ago

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