Subbarao Kambhampati (కంభంపాటి సుబ్బారావు)
rao2z.bsky.social
Subbarao Kambhampati (కంభంపాటి సుబ్బారావు)
@rao2z.bsky.social
AI researcher & teacher at SCAI, ASU. Former President of AAAI & Chair of AAAS Sec T. Here to tweach #AI. YouTube Ch: http://bit.ly/38twrAV Twitter: rao2z
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A meta list of all my 2024 #SundayHarangue's

Not quite sure why, but I apparently wrote sixteen long #AI related Sunday Harangues in 2024.. 😅.

Most were first posted on twitter.

👉https://x.com/rao2z/status/1873214567091966189
Sorry, but I think you miss the point that most of the reasoning model revolution came exactly for tasks where there are verifiers--whether external/symbolic, or learned, or even hand-coded simulators. What do you think RLVR or Self Distillation are?
February 14, 2026 at 4:25 AM
The lectures, 3hrs long with Q&A, are quite up-to-date and cover LLMs, LRMs, as well as the latest test-time scaling and post-training methods such as LLM-Process-Modulo and self-distillation.
February 13, 2026 at 3:31 PM
Here are the recordings of two lectures on 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 & 𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝗖𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 𝗼𝗳 𝗟𝗟𝗠𝘀/𝗟𝗥𝗠𝘀 that I gave this week at Melbourne ML Summer School (lnkd.in/g7rxg9sw).

𝙇𝙚𝙘𝙩𝙪𝙧𝙚 1: youtube.com/watch?v=_PPV...
𝙇𝙚𝙘𝙩𝙪𝙧𝙚 2: youtube.com/watch?v=fKlm...
February 13, 2026 at 3:31 PM
Slides available with the video (direct link bit.ly/4sXyjtj)
January 28, 2026 at 1:07 PM
A common theme in our work these past few years has been pushing back on facile anthropomorphizations (and/or efforts that bring questionable/discredited Cognitive Science metaphors) to LLMs.. So I enjoyed giving this talk at @ivado.bsky.social yesterday... www.youtube.com/watch?v=CoyS...
Anthropomorphization Sins in Modern AI (or Perils of Prematurely Applying Lens of Cognition to LLMs)
YouTube video by Subbarao Kambhampati
www.youtube.com
January 28, 2026 at 1:03 PM
Three of my talks in India last month--at @iitdelhi.bsky.social,
@msftresearch.bsky.social India and at IndoML Symposium--were "On the Mythos of LRM Thinking Tokens." Here is a recording of one of them--the talk I gave at MSR India.

www.youtube.com/watch?v=fCQX...
On the Mythos of LRM "Thinking Tokens" (Talk @ Microsoft Research, India; 12/16/2025)
YouTube video by Subbarao Kambhampati
www.youtube.com
January 6, 2026 at 9:44 PM
Like I say, if a human--even a Terence Tao--makes an egregious mistake (e.g. the one below) once, our trust in them takes a nose dive. With LLMs, it is just "..but they do so well on IMO problems!"..
December 28, 2025 at 3:23 PM
ICYMI, here is my keynote on the semantics of LRM "thinking traces" at #NeurIPS2025 workshop on Multimodal Algorithmic Reasoning. It's a unified view of the seven papers we presented at the conference workshops. Special thanks to the engaged audience..🙏

www.youtube.com/watch?v=rvby...
Talk on the semantics of "Thinking Traces" (Keynote at NeurIPS2025 MAR Workshop)
YouTube video by Subbarao Kambhampati
www.youtube.com
December 9, 2025 at 1:11 PM
[On using Continuous Latent Space Vectors in the context windows of Transformers and LLMs] #SundayHarangue
👉 x.com/rao2z/status...
November 3, 2025 at 3:16 PM
My talk at Samsung AI Forum yesterday
www.youtube.com/watch?v=L2nA...
LRMs and Agentic AI (Talk at Samsung AI Forum)
YouTube video by Subbarao Kambhampati
www.youtube.com
September 16, 2025 at 5:39 PM
In the year since LRMs ("reasoning models") hit the scene, we have been trying to understand, analyze and demystify them.. Here are our efforts to date--conveniently all in one place..👇

www.linkedin.com/posts/subbar...
In the year since LRMs ("reasoning models") hit the scene, we have been trying to understand, analyze and demystify them.. Here are our efforts to date--conveniently all in one… | Subbarao K...
In the year since LRMs ("reasoning models") hit the scene, we have been trying to understand, analyze and demystify them.. Here are our efforts to date--conveniently all in one place.. (𝗙𝗶𝗿𝘀𝘁..) 𝗘𝘃𝗮𝗹...
www.linkedin.com
September 14, 2025 at 10:00 PM
𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐯𝐞 𝐓𝐡𝐢𝐧𝐤𝐢𝐧𝐠? The anthropomorphization of LRM intermediate tokens as thinking begat a cottage industry to "get efficiency by shortening thinking." We ask: 𝗜𝘀 𝗖𝗼𝗧 𝗹𝗲𝗻𝗴𝘁𝗵 𝗿𝗲𝗮𝗹𝗹𝘆 𝗮 𝗿𝗲𝗳𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗵𝗮𝗿𝗱𝗻𝗲𝘀𝘀 𝗼𝗿 𝗶𝘀 𝗶𝘁 𝗺𝗼𝗿𝗲 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝘃𝗲? 👉 www.linkedin.com/posts/subbar...
September 10, 2025 at 4:50 PM
Both LLMs and LRMs are upper bounded by humanity's knowledge closure. True scientific discoveries are, by definition, outside of that closure. Ergo, LLMs/LRMs are great force multipliers to us; but don't support "Nobel this weekend" hype..

👉 www.linkedin.com/posts/subbar...
Neither LLMs nor LRMs have the ability to go beyond the humanity's knowledge closure--which is needed for true discoveries. | Subbarao Kambhampati
Neither LLMs nor LRMs have the ability to go beyond the humanity's knowledge closure--which is needed for true discoveries. Both are beholden to the collected knowledge of the humanity (whether de...
www.linkedin.com
July 19, 2025 at 10:18 PM
Computational Complexity is the wrong measure for LRMs (as it was for LLMs)--think distributional distance instead #SundayHarangue (yes, we're back!)

👉 x.com/rao2z/status...
July 13, 2025 at 9:42 PM
A̶̶̶I̶̶̶ ̶ ̶ ̶ ̶(̶A̶r̶t̶i̶f̶i̶c̶i̶a̶l̶ ̶I̶n̶t̶e̶l̶l̶i̶g̶e̶n̶c̶e̶)̶
̶̶̶A̶̶̶G̶̶̶I̶̶̶ ̶(̶A̶r̶t̶i̶f̶i̶c̶i̶a̶l̶ ̶G̶e̶n̶e̶r̶a̶l̶ ̶I̶n̶t̶e̶l̶l̶i̶g̶e̶n̶c̶e̶)̶
̶̶̶A̶̶̶S̶̶̶I̶̶̶ ̶(̶A̶r̶t̶i̶f̶i̶c̶i̶a̶l̶ ̶S̶u̶p̶e̶r̶ ̶I̶n̶t̶e̶l̶l̶i̶g̶e̶n̶c̶e̶)
ASDI (Artificial Super Duper Intelligence)

Don't get stuck with yesterday's hypeonyms!
Dare to get to the next level!

#AIAphorisms
June 23, 2025 at 10:36 PM
This series of lectures was given the same week there was all that brouhaha over the Apple illusion paper (I was giving these lectures during the day and talking to reporters in the evening 😅). As such they are pretty up-to-date! 3/

x.com/rao2z/status...
Subbarao Kambhampati (కంభంపాటి సుబ్బారావు) on X: "Some of what that recent Apple LRM limitations paper shows is known (pardon my friendly Schmidhubering; I do welcome more LLM studies with scientific skepticism). Our study 👇 from Sep 2024 shows o1 accuracy degrading as complexity increases.. 1/ https://t.co/d8zEUGi4SZ" / X
Some of what that recent Apple LRM limitations paper shows is known (pardon my friendly Schmidhubering; I do welcome more LLM studies with scientific skepticism). Our study 👇 from Sep 2024 shows o1 accuracy degrading as complexity increases.. 1/ https://t.co/d8zEUGi4SZ
x.com
June 19, 2025 at 10:27 PM
The lectures start with a "big picture" overview (Lecture 1); focus on standard LLMs and their limitations, and LLM-Modulo as a test-time scaling approach (Lecture 2); and end with a critical appraisal of the test-time scaling and RL post-training techniques (Lecture 3). 2/
June 19, 2025 at 10:27 PM
For anyone interested, here are the videos of the three ~50min each lectures on the reasoning/planning capabilities of LLMs/LRMs that I gave at #ACDL2025 in Riva Del Sole resort last week. 1/

www.youtube.com/playlist?lis...
ACDL Summer School Lectures on Planning/Reasoning Abilities of LLMs/LRMs - YouTube
www.youtube.com
June 19, 2025 at 10:27 PM
Reposted by Subbarao Kambhampati (కంభంపాటి సుబ్బారావు)
...it basically confirmed what is already well-established: LLMs (& LRMs & "LLM agents") have trouble w/ problems that require many steps of reasoning/planning.

See, e.g., lots of recent papers by Subbarao Kambhampati's group at ASU. (2/2)
June 9, 2025 at 10:53 PM
An AGI-wannabe reasoning model whining that it couldn't handle a problem because its context window isn't big enough is like a superman-wannabe little kid protesting that he couldn't add those numbers because he doesn't have enough fingers and toes.. #AIAphorisms
June 16, 2025 at 12:47 AM
Reposted by Subbarao Kambhampati (కంభంపాటి సుబ్బారావు)
"our counter-intuitive results demonstrate ways in which common interpretations of Large Reasoning Models may be anthropomorphizations or simplifications" arxiv.org/abs/2505.13775
Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens
Recent impressive results from large reasoning models have been interpreted as a triumph of Chain of Thought (CoT), and especially of the process of training on CoTs sampled from base LLMs in order to...
arxiv.org
June 1, 2025 at 1:30 PM
The transformer expressiveness results are often a bit of a red herring as there tends to be a huge gap between what can be expressed in transformers, and what can be learned with gradient descent. Mind the Gap, a new paper with
Lucas Saldyt dives deeper into this issue 👇👇

x.com/SaldytLucas/...
Lucas Saldyt on X: "Neural networks can express more than they learn, creating expressivity-trainability gaps. Our paper, “Mind The Gap,” shows neural networks best learn parallel algorithms, and analyzes gaps in faithfulness and effectiveness. @rao2z https://t.co/8YjxPkXFu0" / X
Neural networks can express more than they learn, creating expressivity-trainability gaps. Our paper, “Mind The Gap,” shows neural networks best learn parallel algorithms, and analyzes gaps in faithfulness and effectiveness. @rao2z https://t.co/8YjxPkXFu0
x.com
May 30, 2025 at 1:59 PM
Anthropomorphization of intermediate tokens as reasoning/thinking traces isn't quite a harmless fad, and may be pushing LRM research into questionable directions.. So we decided to put together a more complete argument. Paper 👉 arxiv.org/pdf/2504.09762 (Twitter thread: x.com/rao2z/status...)
May 28, 2025 at 1:41 PM