Knowledge catalogue
arXiv:2601.22652v2 Announce Type: replace-cross Abstract: Spectral gradient methods, such as the Muon optimizer, modify gradient updates by preserving directional information while discarding scale, a
arXiv:2603.20659v2 Announce Type: replace Abstract: Large scale pre-training on text and image data along with diverse robot demonstrations has helped Vision Language Action models (VLAs) to generaliz
arXiv:2607.04963v1 Announce Type: new Abstract: Reinforcement Learning (RL) is the dominant paradigm for training Large Language Model (LLM) agents on long-horizon tasks. However, sparse and delayed r
States are asking for a $1.4 trillion fine of Meta over addicting kids. Basically they are saying Facebook's business model is a result of crime, and all of Mark Zuckerberg's property should be forfei
arXiv:2607.05264v1 Announce Type: new Abstract: Existing video benchmarks evaluate action recognition on consumer videos, egocentric recordings, or simulated industrial environments. They do not test
arXiv:2607.04708v1 Announce Type: cross Abstract: Agentic AI is shifting online shopping from search toward delegated purchasing, where autonomous buying agents monitor markets and decide when to buy
arXiv:2607.03501v1 Announce Type: cross Abstract: Copernicus, the European Union's Earth observation program, produces petabytes of Earth observation and climate data, offering immense potential for r
arXiv:2203.01687v3 Announce Type: replace Abstract: Medical landmark detection usually requires accurate expert annotations, which are laborious and difficult to scale across anatomical regions. In th
arXiv:2510.08048v4 Announce Type: replace-cross Abstract: Query-product relevance prediction is fundamental to e-commerce search and has become even more critical in the era of AI-powered shopping, wh
arXiv:2607.03181v1 Announce Type: cross Abstract: Successful diffusion of AI in the workforce hinges on the economic value that AI brings to human endeavors. Bringing AI into the workforce is more tha
arXiv:2607.04061v1 Announce Type: cross Abstract: Distinguishing Large Language Model (LLM) generated text from human writing is a critical and difficult challenge. While LLMs are trained to write lik
arXiv:2607.03788v1 Announce Type: new Abstract: Discrete diffusion promises orders-of-magnitude faster generation than autoregressive (AR) models for sequential discrete data, yet its full potential o
arXiv:2607.03143v1 Announce Type: cross Abstract: Vision-language alignment powers open-vocabulary recognition, retrieval, and LVLM grounding, yet natural captions are often underspecified, making sim
arXiv:2606.22726v2 Announce Type: replace Abstract: Choreographic motion generation poses unique challenges for AI, demanding precise semantic control over complex, temporally structured, and expressi
arXiv:2607.02615v1 Announce Type: cross Abstract: Generating structured artifacts with Large Language Models - e.g. database queries, threat framework mappings, entity schemas - is relatively straight
The AI boom is just not sustainable; Apollo’s Torsten Slok joins the chorus. Torsten Slok argues that the AI boom can only be seen in the hyperscalers and semiconductor companies and that this is caus
arXiv:2607.02955v1 Announce Type: cross Abstract: We argue that AI systems used in conducting foreign policy tasks - broadly enacting 'statecraft' - should be a priority test case for technical AI gov
Written by: Shebin Mathew Introduction The 'Golden SAML' technique, first described by CyberArk researchers in 2017, and further detailed by Mandiant researchers in 2021, remains one of the most effec
arXiv:2510.01460v4 Announce Type: replace-cross Abstract: Offline-to-online reinforcement learning (RL) has emerged as a practical paradigm that leverages offline datasets for pretraining and online i
arXiv:2607.03928v1 Announce Type: cross Abstract: Accent normalization (AN) seeks to convert non-native (L2) accented speech into standard (L1) speech while preserving speaker identity. The current te
arXiv:2509.01251v3 Announce Type: replace Abstract: This paper presents a joint effort towards the development of a data-driven Social Robot Navigation metric to facilitate benchmarking and policy opt
arXiv:2607.04745v1 Announce Type: cross Abstract: Modern thermal visual place recognition (TIR-VPR) frontends based on foundation models achieve remarkable closed-set retrieval but suffer from an over
arXiv:2511.13103v2 Announce Type: replace Abstract: Multi-agent reinforcement learning (MARL) has shown promise for large-scale network control, yet existing methods face two major limitations. First,
arXiv:2607.04751v1 Announce Type: cross Abstract: Big goals are hard to achieve all at once; breaking them into small steps is wiser. We present Trust Region Policy Distillation (TOP-D), which transfo
arXiv:2607.04728v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training for large language models (LLMs) follows a efficient paradigm of 'rollout then update', which inevitably res
arXiv:2607.04487v1 Announce Type: cross Abstract: Neural autoregressive solvers for the Multi-Attribute Vehicle Routing Problem (MAVRP) reach competitive cost but offer no per-step justification, a pr
arXiv:2607.04425v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models and agent systems have driven GUI agents from single-platform task execution toward cross-platform int
arXiv:2607.04430v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in question answering (QA) systems, yet they may generate hallucinated or misaligned responses wi
arXiv:2607.04984v1 Announce Type: new Abstract: Continual Generalized Category Discovery (C-GCD) aims to incrementally identify novel categories from sequential unlabeled data while preserving recogni
arXiv:2607.03589v1 Announce Type: new Abstract: State Space Models (SSMs) have emerged as an alternative to Vision Transformers, yet most vision SSMs inherit directional token scanning from causal seq
arXiv:2508.08521v2 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) are increasingly being used in a broad range of applications, bringing their security and behavioral control to
arXiv:2607.04517v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are commonly treated as end-to-end action policies conditioned on natural-language task descriptions. In practice, h
arXiv:2607.05394v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is a powerful recipe for improving language-model reasoning, but it is expensive to repeat on ev
Who is entitled to benefit from major advances in technology—and on what basis? This new paper with @Dr_Atoosa argues that the benefits of technology—including AI—belong to the world in the sense that
arXiv:2607.04879v1 Announce Type: new Abstract: Although multi-source fusion positioning systems have achieved significant progress, accurate and reliable heading estimation remains a critical challen
⚠️ Wow. The Treasury Department reportedly knows that the massive GenAI build out poses systemic risks to the US financial system – and doesn’t want to acknowledge it publicly. People may talk about t
You don't have to choose between 'AI is fake hype' and 'Superintelligence is inevitable, lie down and accept it.' There's a third option: humans deciding, through their governments, that machines smar
A CEO who “vowed to fire anyone who doesn’t use AI in 2025” now says AI could not replace her executive assistant. This says a lot about how many big believers in AI have realized that AI is not as go
Gary Marcus argues that Geoff Hinton, rather than Dario Amodei, was the originator of making exaggerated claims about neural networks' impact on employment. This appears to be part of a broader discus
GenAI isn’t good enough to replace millions of employees, so there is basically no way the capex is going to earn out. If AI isn't going to wipe out millions of jobs every year, it has to generate pro
ha ha Geoff Hinton in 2016 completely overhyping where deep learning was at then Geoffrey Hinton explains the coyote test for medical AI: radiology is already over the cliff, it just has not looked do
Hugging Face has just been sued for alleged copyright infringement for hosting & distributing copyrighted images, used for AI training. It's been almost a *year* since I flagged to their CEO that they
I cannot believe how good GLM 5.2 is. Several weeks in now and it's mostly all I have been using. It doesn't have the alignment issue of cloud AI, it's much more clear what it can do and can't because
If that happens, where does it leave Anthropic and OpenAI? And Oracle, CoreWeave, Nebius, xAI, etc? Fable 5 probably running locally in about two years. That is the projection in this r/LocalLLaMA cha
This article likely explores the concept of robustness in AI systems and what it means for AI to be 'robust to' various types of failures, adversarial inputs, or distribution shifts. The piece probabl
Gary Marcus reflects on his 2023 prediction that large language models would become commoditized, noting that this outcome is now materializing. The post suggests that LLMs are transitioning from nove
this is a bit confused. should I unpack it? tl;dr LLMs are already neurosymbolic in its latent space this is the mechanistic explanation for the intuitively obvious 'feel' that the stochastic parrot c
Trump blockading Cuba into catastrophe should be a much bigger story than it is. Cuba’s electric grid suffered a total collapse Monday as the nation struggles with crumbling infrastructure and a de fa
unconscionable, if these death numbers are even vaguely correct update: https://www.doge-impact.org suggests that the actual number is over 1M; the number below is just USAID related. Money saved: 0 P
when capex quadruples relative to revenue in five years it just can’t be good. FT: 'It is not yet clear that either [OpenAI or Anthropic] has a sustainable business model. For sure, both have built as
When I talk to people that instantly, deeply, get the risk from superintelligence, they often share a trait sometimes called the 'security mindset' I think this post by @l_mc_nally is a nice brisk tou
“AI is now costing some companies more than the people it was supposed to replace.” I think AI is in a messy middle phase where usage looks productive, but output remains unclear. Forbes published thi
Josh Zoffer / Financial Times: Data centers offer US a chance to get ahead in the next key technologies and to build domestic supply chains based on demand rather than subsidies and tariffs — America
Gary Marcus argues that Elon Musk's public opposition to democracy reveals important truths about how extreme wealth concentrates power and can lead wealthy individuals to reject democratic principles
Junk food is an interesting failure of capitalism. We exchanged human beauty for cheetos. Bryan Caplan types are forced to think this trade a worthy one. None born before the obesity crisis would have
Pop quiz: Can you explain the contrast here, between AI’s coding ability and their less compelling research ability? AI's coding ability has become amazing. But there research ability remains really p
This post appears to reference an unusual weather event (lightning) as symbolic proof that the United States retains geopolitical dominance or divine favor, likely in the context of discussions about
Connor Leahy posted about reaching 250 of something, likely a milestone related to followers, users, or members based on the celebratory phrasing 'To 250 more!' The post appears to be a brief celebrat
true. a lot of people here just don’t have the historical context. You know what's funny but not funny: If the housing market of 2006 was the AI market of 2026, Charles R Morris would be getting calle
DOGE deletes itself on July 4th. It will be remembered as a hugely destructive failure. Musk promised 2 trillion in savings. What we got, by DOGE’s own unverified math, was 215 billion. Even that numb