Calling all parsimony and learning researchers π¨π¨ The 3rd annual CPAL will be held in TΓΌbingen Germany March 23β26, 2026! Check out this year's website for all the details cpal.cc
23.09.2025 14:22 β π 3 π 1 π¬ 0 π 1@atlaswang.bsky.social
https://www.vita-group.space/ π¨βπ« UT Austin ML Professor (on leave) https://www.xtxmarkets.com/ π¦ XTX Markets Research Director (NYC AI Lab) Superpower is trying everything πͺ Newest focus: training next-generation super intelligence - Preview above πΆ
Calling all parsimony and learning researchers π¨π¨ The 3rd annual CPAL will be held in TΓΌbingen Germany March 23β26, 2026! Check out this year's website for all the details cpal.cc
23.09.2025 14:22 β π 3 π 1 π¬ 0 π 1Got a comment I secretly like:
βThis professor is constructively rudeβ
Paying for a dinner I wasnβt even at π€£ β momentumβs strong, keep it up team!
www.vita-group.space/team
I really wanna see / do research on using AI to prevent massive shooting β¦
27.08.2025 16:05 β π 1 π 0 π¬ 0 π 0Perhaps Iβm not alone in feeling GPT5 (even pro) is no better than o3-proβ¦ coding and knowledge?
08.08.2025 20:18 β π 1 π 0 π¬ 1 π 0www.linkedin.com/posts/atlas-...
Cannot resist enjoying some proud advisor moment
Two fresh tutorials on low-dimensional DL:
Sparsity β23 π vita-group.github.io/SparsityTuto...
Low-Rank β25 π vita-group.github.io/LowrankTutor...
Curious about how sparsity and low-rank ideas power modern deep learning? I hope these slide decks & notes are a useful starting point! π
Of all my studentsβ career achievements, this one makes me proudest: because really, who needs yet another AI professor or scientist alumni when you can boast a professional cat-breeder student?
www.bestbritishcats.com To my Bay Area friends: BUY one!
Maybe try using my name to get a discount :)
Practically, enforce the right symmetries + keep weight distributions low-entropy-> you may get symbolic generalization βfor free.β Lines up with grokking & reasoning-finetuning we keep seeing.
If emergent reasoning, implicit alignment, or theory-catching-practice excites you, dive in & poke holes!
Key ideas:
β’ #EmergentReasoning β provably, no external logic engine needed.
β’ #GeometricLens β lift weights to a probability measure & watch training as a Wasserstein gradient flow; messy SGD turns into clean geometry.
β’ #Compositionality β small rules snap into big ones. (3/n)
Why the hype? It gives a principled story for how discrete, symbolic #reasoning can emerge inside a vanilla neural net trained with plain gradients. Continuous weights β spontaneous symbolic rules. Mathy yet hopefully still readable (2/n).
30.06.2025 10:09 β π 0 π 0 π¬ 1 π 0@talkachman.bsky.social caught it faster before I did... but here we go!
π New pre-print dropped lnkd.in/gmQ9hBdf
Its first draft won the #DARPA Disruptive Idea award at #NeuS2025. Now my student Peihao Wang has sharpened the theory even more. Iβm so excited what it means for AI reasoning π§©π€ (1/n)
@atlaswang.bsky.social knocking out of the park again!
half a page in and this is a phenomenal read. So much to wrap my head around
www.arxiv.org/abs/2506.21797
aha thanks! So fast you are
30.06.2025 09:50 β π 0 π 0 π¬ 1 π 0Feels great relief to report: #Thrilledtoshare (yes, that LinkedIn tone I hate...) we have 0 papers accepted to @iccv.bsky.social !
Surprisingly liberating to step off the number game: I meant it.
Iβm genuinely proud of the science my students are building, no matter how ICCV reviewers think π€£
Figure 4. Task-Specific ViewRelevance
An #AI system that automatically interprets echocardiograms maintained high accuracy across geography and time from complete and limited studies.
https://ja.ma/4jYWBgI
Check out #PanEcho, now in @jama.com
β
open weights
β
multiview multitask reporting
β
international validation
β
works with POCUS
Amazing effort @cardslab.bsky.social
@giholste.bsky.social @rohankhera.bsky.social
+ @atlaswang.bsky.social, MΓ‘rton Tokodi & Attila KovΓ‘cs
#CardioSky #EchoSky
A reflection sparked by Saturday nightβs thought-provoking dinner conversation π₯
www.linkedin.com/pulse/beyond...
Making a new website of my research group, and did a visualization of all our papers from 2018 to present: clustered into 10 topics.
One can clearly see how this group evolves its own tastes!
β¦ and deeper in my heart: long live optimization!! β€οΈ
Quoting one slides from @yann-lecun.bsky.social talkβ¦
arxiv is filled by papers that treat symptoms (or not even!) without ever diagnosing the disease
Unwelcome idea: Iβm extremely tired of seeing one more LLM paper and believe academics shall pivot away from this area.
So boring arxiv feeds every dayβ¦
This is going to kneecap science in this country for years. www.nature.com/articles/d41...
02.05.2025 03:52 β π 5 π 3 π¬ 1 π 0One of my PhD students got their visa revoked. I know of other cases amongst my AI colleagues. This is not what investing in US leadership in AI looks like.
www.aljazeera.com/news/2025/4/...
π Thrilled to announce SPIN-Bench!π
We all love seeing how smart LLMs can be-solving complex math, crafting beautiful text, and coding effortlessly. But how well do they handle real-world strategic complexity, cooperation, & social negotiation? Can they play well when things get tricky?
Not quite!
Just had a meal that gifted me two rare treasures:
1οΈβ£ Meeting someone infinitely wiser than me.
2οΈβ£ They werenβt cold or meanβjust gently showed me where I could grow.
"To learn truth at dawn, Iβd die content by dusk."
β¨ Humility tastes better with kindness. #Gratitude #LifeLessons
Good news? SPIN-Bench pinpoints exactly where these models fall shortβand illuminates exciting research directions to smarter, socially savvy AI
For some extra fun (and detailed, interactive trajectory visualizations!), visit project pageοΌ
π spinbench.github.io
full paper: arxiv.org/pdf/2503.12349
π Diplomacy β The ultimate testοΌ Models had to negotiate, forge alliances, and occasionally backstab. Result? Even the best LLMs floundered, struggling to juggle complex social interactions and strategic depth.
18.03.2025 11:18 β π 2 π 1 π¬ 1 π 0π΄ Cooperative Games (Hanabi): Coordination among teammates dramatically challenges models, causing their performance to dip sharply as complexity ramps up. Turns out, keeping track of your teammatesβ intentions isnβt an easy taskβeven for GPTs!
18.03.2025 11:18 β π 1 π 1 π¬ 1 π 0Results fascinatingly reveal:
πΉ Classic Planning: LLMs ace simpler puzzles but struggle badly as complexity growsβlosing track at longer-term decisions
π Competitive Games: Top chess engines swept every LLM clean. Even simple tactical awareness quickly fades when facing deeper strategic branches