Krishna Balasubramanian

201 posts

Krishna Balasubramanian

Krishna Balasubramanian

@krizna_b

Associate professor at @ucdavis, Amazon (AWS) scholar

Katılım Mart 2020
536 Takip Edilen733 Takipçiler
Krishna Balasubramanian
Krishna Balasubramanian@krizna_b·
so many words to say "I don't know" 😂
Andrew Curran@AndrewCurran_

Terence Tao responding to a question on what advice he would give someone considering a career in math in 2026: 'Yeah, so we live in a time of change. It is, as I said, we live in a particularly unpredictable era. And I think things that we've taken for granted for centuries may not hold anymore. So, yeah, the way we... do everything, not just mathematics, will change. In many ways, I would prefer the much more boring, quiet era where things are much the same as they were 10 years ago, 20 years ago. But I think one just has to embrace that there's going to be a lot of change and that, you know, the things that you study, some of them may become obsolete or revolutionized, but some things will be retained. There'll be a lot of opportunities for things that you wouldn't be able to do before. So, I mean, in math, you previously had to basically go through years and years of education to be a math PhD before you could contribute to the frontier of math research. But now it's quite possible at the high school level or whatever, that you could get involved in a math project and actually make a real contribution because of all these AI tools and lean and everything else. So there'll be a lot of non-traditional opportunities to learn. So you need a very adaptable mindset. There'll be one for pursuing things just for curiosity, for playing around. And I mean, you still need to get your credentials. I mean, I think for a while it would still be important to sort of still go through traditional education and learn math and science and so forth the old-fashioned way for a while. Yeah, but you should also be open to very, very different ways of doing science, some of which don't exist yet. Yeah, so it's a scary time, but also very exciting.'

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Krishna Balasubramanian
Krishna Balasubramanian@krizna_b·
Summary from the paper: • Forward-KL (SFT) → ❌ mass forgetting • Reverse-KL (RL) → ✅ preserves old behavior • SDFT / TTT-Discover / OAPL → partial or conditional protection
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Krishna Balasubramanian@krizna_b·
🚨 When and why does post-training cause LLMs to forget? We answer this question quantitively in our new paper, and analyze recent methods like Self-Distillation Fine-Tuning (SDFT), Test-Time Training to Discover (TTT-Discover) and Optimal Advantage-based PO with Lag (OAPL)
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Stat.ML Papers
Stat.ML Papers@StatMLPapers·
A Quantitative Characterization of Forgetting in Post-Training ift.tt/YXJPIOc
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Damek
Damek@damekdavis·
On what day do you think @OpenAI will announce they solved all the "first proof" problems?
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Weijie Su
Weijie Su@weijie444·
It is my tremendous honor and privilege to receive the 2026 COPSS Presidents' Award. Statistics is powerful and will only grow more vital in the AI age. Grateful to my mentors, collaborators, colleagues, and students who made this journey possible.
The Wharton School@Wharton

Congratulations to Prof. Weijie Su (@weijie444) from our Statistics and Data Science Department on being named the recipient of this year's Committee of Presidents of Statistical Societies (@COPSSNews) Presidents' Award: whr.tn/3ZToJu9 The honor is given annually to a young member of the statistical community in recognition of outstanding contributions to the profession of statistics. It's jointly sponsored by five statistical societies: @AmstatNews, @ENAR_ibs, @InstMathStat, @SSC_stat, and @WNAR_ibs.

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Statistics (Machine Learning) Papers
Dependence-Aware Label Aggregation for LLM-as-a-Judge via Ising Models Krishnakumar Balasubramanian, Aleksandr Podkopaev, Shiva Prasad Kasiviswanathan arxiv.org/abs/2601.22336 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚜𝚝𝚊𝚝.𝙼𝙴]
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Dmitry Krotov
Dmitry Krotov@DimaKrotov·
Now that ICML papers are submitted, what could be a better time to prepare a cool paper for the New Frontiers in Associative Memory workshop @iclr_conf? Deadline: February 14, 2026.  Call for papers: nfam2026.amemory.net. Submissions are open via Open Review: openreview.net/group?id=ICLR.….   Join Associative Memory enthusiasts in Rio de Janeiro!
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Dmitry Krotov
Dmitry Krotov@DimaKrotov·
Official #ICLR2026 workshop on Associative Memory! The scope covers algorithms, architectures, hardware design, agentic workflows, and other ideas where memory plays crucial computational role. The call for contributed papers is now open via Open Review. Please consider submitting your best work and join us in sunny📍Rio de Janeiro! The lineup of invites speakers is amazing: Jay McClelland, Xueyan Niu, Paul Liang (@pliang279 ), Meisam Razaviyayn (@meisamrr), Natalia Berloff, David Clark (@d_g_clark), and others. There will also be exciting panel discussions.
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Julia Kempe
Julia Kempe@KempeLab·
Excited to co-organise! 🧠 New Frontiers in Associative Memories 2026 @iclr_conf How do memory, attention, energy landscapes, and generative models connect? Submit your papers by 2/14! Details: 🔗 nfam2026.amemory.net 📷Rio de Janeiro | Apr 26–27, 2026 #NFAM2026 #ICLR2026
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Krishna Balasubramanian
Krishna Balasubramanian@krizna_b·
🧠 New Frontiers in Associative Memories 2026 @iclr_conf How do memory, attention, energy landscapes, and generative models connect? We’re bringing together theory + practice on associative memory as a core AI primitive. 📍Rio de Janeiro | Apr 26–27, 2026 #NFAM2026 #ICLR2026
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