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Computer Vision and Pattern Recognition News

Katılım Eylül 2018
729 Takip Edilen14.8K Takipçiler
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Haider.
Haider.@slow_developer·
Yann LeCun says today's humanoid robot demos look impressive, but the robots are very stupid in the real world "the missing piece is not hardware; it is AI that can't reason, plan, or adapt like humans" Robot companies are betting AI will make them smart enough to sell at scale within 3-5 years It's a big bet
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M. Alex O. Vasilescu
M. Alex O. Vasilescu@AlexTensor·
Ironically, #AI was supposed to accelerate research. Instead, it is slowing it down. One side effect of #LLMs is synonym churn for concepts that already have well-established names. LLMs do not understand that technical disciplines rely on precise, established terminology, not endless rewording. As a result, we are producing papers in which the only novelty is the vocabulary. There ought to be a penalty for that.
Yi Ma@YiMaTweets

In system theory, it is called "linearization"... which has been studied and used for decades. Honestly, folks, there is no need to invent or introduce any new terminology. Remember, there is rarely anything new under the sun...

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Steven Pinker
Steven Pinker@sapinker·
Ways in which Large Language Models differ from human inteligence, by @garymarcus and collaborators.
Valerio Capraro@ValerioCapraro

Here's the longer version of our Nature piece. Our argument is simple: statistical approximation is not the same thing as intelligence. Strong benchmark scores often say very little about how LLMs behave under novelty, uncertainty, or shifting goals. Even more importantly, similar behaviors can arise from fundamentally different processes. In another paper, we identified seven epistemological fault lines between humans and LLMs. For example, LLMs have no internal representation of what is true. They often generate confident contradictions, especially in longer interactions, because they do not track what is actually true. Another example. Yes, LLMs have solved some open mathematical problems, but these cases typically involve applying known methods to well-defined problems. LLMs cannot invent anything that is truly new and true at the same time, because they lack the epistemic machinery to determine what is true. None of this means LLMs are useless. Quite the opposite: they are extraordinarily useful. But we should be careful about what they are and what they are not. Producing plausible text is not the same as understanding. Statistical prediction is not the same as intelligence. So despite the hype from the usual suspects, AGI has not been achieved. * paper in the first reply Joint with @Walter4C and @GaryMarcus

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Moshe Vardi
Moshe Vardi@vardi·
Join me in supporting this important cause at iPetitions. Restore Fully Free and Open Access to the ACM Digital L... ipt.io/GWV5J via @ipetitions
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M. Alex O. Vasilescu
M. Alex O. Vasilescu@AlexTensor·
Hype vs Reality: --- Eric Schmidt: my early life was coding; now AI can do almost everything I learned. #AI is “a supercomputer and superprogrammer in your pocket.” Andrej Karpathy: latest project was hand-written because agents were “net unhelpful.” This is a reversal from his “vibe coding” era. Vibe coding is a term he coined in Feb. 2025. timesofindia.indiatimes.com/technology/tec…
Rohan Paul@rohanpaul_ai

Google's ex-CEO Eric Schmidt talks about how his whole early life was basically coding, and how AI just wiped it out. He says in his 20s all he wanted to do was write programs, all the way through college and grad school, and that this is what built his career. But now, every single thing he learned back then can be done by AI. "Each and every one of you has a supercomputer and superprogrammer in your pocket." --- From 'Institute of Politics Harvard Kennedy School' YT channel

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Thomas G. Dietterich
Thomas G. Dietterich@tdietterich·
I'd like to propose the following norm for peer review of papers. If a paper shows clear signs of LLM-generated errors that were not detected by the author, the paper should be immediately rejected. My reasoning: 1/
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#CVPR2026
#CVPR2026@CVPR·
CVPR 2026 Registration is now live! Please remember if you have a paper accepted, you must register as an author. Anyone is welcome to attend CVPR as long as they are registered before arriving onsite. cvent.me/dMoWob
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#CVPR2026
#CVPR2026@CVPR·
Our #CVPR2026 Program Chairs have just pushed out a follow-up email with clarifications. Check your email (and spam folder).
#CVPR2026 tweet media#CVPR2026 tweet media
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#CVPR2026
#CVPR2026@CVPR·
The #CVPR2026 workshop proposal decisions have been sent via email to the organizers and are also available on OpenReview.
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Deblina Bhattacharjee
Deblina Bhattacharjee@deblinaforAI·
The AI for Visual Arts @AI4VAWorkshop will return for its 3rd edition to @CVPR 2026 in Denver 🎨💻! We will have both long (archival) papers appearing in the CVPR workshop proceedings and short (non-archival) ones. We will also arrange a visit to the Denver Museum! Stay tuned!
Deblina Bhattacharjee tweet media
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Chan Hee (Luke) Song
Chan Hee (Luke) Song@luke_ch_song·
🎉 Embodied Reasoning in Action (ERA) Workshop is coming to @CVPR 2026! We have an exciting list of speakers on reasoning for robotic manipulation, spanning spatial relations, affordances, dynamics, causality, and language-grounded action. We will also host two challenges based on RoboSpatial and PointArena. Website: embodied-reasoning.github.io Organizers: @DJiafei @RenZhongzheng @hq_fang @TonyWentaoYuan @YiruHelenWang @ziqiao_ma @YejinKim4 @mayasguru and Dieter Fox
Chan Hee (Luke) Song tweet media
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Hirokatsu Kataoka | 片岡裕雄
Hirokatsu Kataoka | 片岡裕雄@HirokatuKataoka·
#CVPR2026 VGI Workshop のサポーターとして JST ASPIRE からご承認頂きました。ロゴも website 中に掲載しています。 CVPR 2026 VGI Workshop: cvpr2026-vgi-workshop.limitlab.xyz ASPIRE: jst.go.jp/aspire/
Hirokatsu Kataoka | 片岡裕雄 tweet media
Hirokatsu Kataoka | 片岡裕雄@HirokatuKataoka

[#CVPR2026 Workshop] Excited to announce that our workshop "Visual General Intelligence (VGI): Vision Research Toward the AGI Era" has been accepted at CVPR 2026! Please also check out the website & blog post! Website: cvpr2026-vgi-workshop.limitlab.xyz Blog post: hirokatsukataoka.medium.com/vision-researc…

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Haider.
Haider.@slow_developer·
Yann LeCun says we're fooled by LLMs because they manipulate language well, and we associate that with intelligence But language fluency doesn't mean underlying intelligence Every generation since the 1950s claimed its technique was the ticket to human-level AI All were wrong. "this generation with LLMs is also wrong"
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