Sílvia Casacuberta

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Sílvia Casacuberta

Sílvia Casacuberta

@SiCaPu

CS PhD student & @KnightHennessy scholar @Stanford. Prev.: @UniofOxford with @rhodes_trust, @Harvard '23, @MPI_IS, @CSatETH, @IBM. Theory CS for Trustworthy AI

Katılım Nisan 2013
2.2K Takip Edilen811 Takipçiler
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Boaz Barak
Boaz Barak@boazbaraktcs·
New award: Trevisan Award for Expository Work. Love the idea of awarding work that explains and illuminates, and it is so fitting way to honor Luca, who was a master explainer. windowsontheory.org/2026/02/05/tre…
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Simons Institute for the Theory of Computing
The successes of generative AI and LLMs involve deep internal representations of the world. In his Theoretically Speaking lecture, Jon Kleinberg explored how these work, and how they relate to the representations of the world that we build as humans. bit.ly/4qE98dO
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Judy Shen
Judy Shen@judyhshen·
📣Our study on how AI impacts coding skill formation is now out! (w. @AlexTamkin) AI Assistance is NOT a shortcut to skill formation. Using AI to help you learn to code only reduces mastery if you’re delegating everything.
Anthropic@AnthropicAI

AI can make work faster, but a fear is that relying on it may make it harder to learn new skills on the job. We ran an experiment with software engineers to learn more. Coding with AI led to a decrease in mastery—but this depended on how people used it. anthropic.com/research/AI-as…

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Quanta Magazine
Quanta Magazine@QuantaMagazine·
To thwart malicious prompts, large language models use filters that are smaller than the models themselves. Recently, the Turing Award-winning cryptographer Shafi Goldwasser and researcher Sarah Ball showed that this size disparity makes LLMs insecure. quantamagazine.org/cryptographers…
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Quanta Magazine
Quanta Magazine@QuantaMagazine·
The researchers Lijie Chen (left), Igor Oliveira (top-right) and Jitau Li recently used “reverse mathematics” to connect a theorem called the pigeonhole principle to a whole class of complexity problems. quantamagazine.org/reverse-mathem…
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Sílvia Casacuberta
Sílvia Casacuberta@SiCaPu·
If you are interested in learning with abstentions (in the predictive or generative setting), calibration, uncertainty quantification, conformal prediction, or any other related topics, I would love to chat! I’ll be in Exhibit Hall C,D,E #3013 this Thursday 11 am - 2 pm PST.
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Sílvia Casacuberta
Sílvia Casacuberta@SiCaPu·
Looking forward to attending #NeurIPS in San Diego this week! I will be presenting our spotlight paper (joint with Varun Kanade) on building predictors that abstain optimally and fairly.
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Preetum Nakkiran
Preetum Nakkiran@PreetumNakkiran·
LLMs are notorious for "hallucinating": producing confident-sounding answers that are entirely wrong. But with the right definitions, we can extract a semantic notion of "confidence" from LLMs, and this confidence turns out to be calibrated out-of-the-box in many settings (!)
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Sarah Cen
Sarah Cen@cen_sarah·
In the AI ecosystem, who supplies the data? the compute? the models? We just released a new tool on the AI Supply Chain. Our dataset reveals how AI models, data, compute, capital, and even talent change hands. Here’s why you should care 👇
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Nikhil Chandak
Nikhil Chandak@nikhilchandak29·
Thinking of doing a PhD/research visit? Consider applying to/visiting @ELLISInst_Tue @MPI_IS. We have PIs doing cool work, great funding, and most importantly, one of the best academic compute: 50+ GB200s, 250+ H100s, and many more A100 80GBs. Come join us!
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Sílvia Casacuberta
Sílvia Casacuberta@SiCaPu·
When we first started thinking about clones for our final project in @ArielProcaccia’s fantastic course on optimized democracy, we couldn’t have anticipated the journey that it would take us on! What a gift to be able to do research with friends
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