Search: “safety”

arXiv:2603.09803v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) improves reasoning in large language models but treats all correct solutions equally, potentia

arXiv:2606.04889v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (e.g. GRPO) is now a common way to improve mathematical reasoning in Large Language Models (LLMs). Howeve

arXiv:2606.04825v1 Announce Type: new Abstract: Despite the importance of tactile sensing for reliable manipulation, most existing Vision-Language-Action (VLA) datasets remain vision-only, and those t

How does Elon get off on just lying straight up about the mainstream media? Can someone like BBC sue him for defamation? He claimed “Legacy mainstream media, same ones who wrote about George Floyd mil

arXiv:2606.04612v1 Announce Type: new Abstract: Large Language Models (LLMs) are vulnerable both to hallucination and adversarial manipulation. Although these problems are closely related, existing de

I think @Levie is overstating the positive case for employment in the (near term) AI era but that most people have overstated the negative case, and that the truth is somewhere in between. Which is to

If we can’t trust Goldman on which IPO to buy… who can we trust? WeWork. Goldman Sachs marketed the real estate firm at an inflated 96 billion dollar tech valuation. The IPO was pulled after the prosp

Gary Marcus poses a hypothetical investment question asking followers to choose among three major IPOs, likely seeking comparative analysis of high-profile public offerings. The post invites discussio

Gary Marcus discusses investment strategy between potential OpenAI and Anthropic IPOs, likely weighing factors such as the companies' technological capabilities, market positioning, business models, a

If you – or your retirement funds - get taken for a ride on SpaceX blame hype guys like this, who don’t even mention that Goldman is the lead left on the deal. GOLDMAN SEES SPACEX AI REVENUE EXPLODING

arXiv:2606.05030v1 Announce Type: new Abstract: Autoregressive chain-of-thought (CoT) reasoning in large language models (LLMs) is fundamentally forward-directed: each step conditions only on prior to

arXiv:2606.05042v1 Announce Type: cross Abstract: Marginal inference in discrete graphical models forces a choice between exactness and scalability: exact algorithms are intractable for high-treewidth

Incredible. Goldman Sachs is the lead left on the SpaceX IPO, and somehow @ft fails to mention this in the headline below 🤦‍♂️ Goldman Sachs expects SpaceX’s AI revenue to surge 100 times by 2030 http

arXiv:2606.04269v1 Announce Type: cross Abstract: Deformable object manipulation (DOM) is challenging due to high-dimensional, partially observable states that evolve through long-horizon, topology-ch

arXiv:2606.04033v1 Announce Type: new Abstract: The validation of advanced nuclear reactor designs and fuel concepts requires critical experiments with high neutronic similarity to the target technolo

It seems like @GaryMarcus was right: the AI revenue models are imploding Sam Altman said AI budgeting has recently become a 'huge issue' for some companies, something that 'never came up' earlier this

Gary Marcus critiques a company's decision to pursue an IPO at a trillion-dollar valuation despite allegedly being on the brink of financial collapse. The post suggests this represents either audaciou

Kinda crazy (but typical, sadly) that some moron just claimed that I was “doomer” who said that all jobs would be replaced when I actually publicly predicted the opposite! Receipt, from my essay “25 p

arXiv:2606.04180v1 Announce Type: new Abstract: Vision-language foundation models such as CLIP and SigLIP provide widely used representations for multimodal learning systems. While these models are ty

La stratégie nationale en matière d’IA dévoilée aujourd’hui prône le développement d’une technologie sécuritaire, éthique, digne de confiance, et bénéfique pour l’ensemble de la société — ce sont les

arXiv:2606.04846v1 Announce Type: new Abstract: As Large Language Models (LLMs) become increasingly popular in educational settings, they raise important questions about the ethical implications of th

arXiv:2411.19758v2 Announce Type: replace-cross Abstract: Remote sensing change detection based on a map reference and an up-to-date image boosts timely observation of the Earth's surface when earlier

arXiv:2606.04815v1 Announce Type: cross Abstract: Lifelong learning is essential for Large Language Model (LLM) agents operating in dynamic, interactive environments. However, existing lifelong learni

arXiv:2606.04829v1 Announce Type: new Abstract: Building a general-purpose whole-body controller is essential for enabling diverse motion capabilities in humanoid robots across a wide range of downstr

arXiv:2510.01532v2 Announce Type: replace Abstract: In semi-supervised segmentation, capturing meaningful semantic structures from unlabeled data is essential. This is particularly challenging in hist

Sarah Perez / TechCrunch: Meta's Oversight Board says Meta's account deactivations lack due process, violations are flagged without clarity, and there's little support for appeals — Meta's Oversight B

arXiv:2606.04413v1 Announce Type: new Abstract: Helpful-only models, that is, models that are trained to always follow user intent, are valuable for dangerous capability evaluations and other areas of

arXiv:2606.04231v1 Announce Type: cross Abstract: Recent advances in multimodal retrieval-augmented generation (MM-RAG) have shifted toward minimal parsing, relying on page-level images for producing

This article discusses methods and tools for evaluating routing policies in machine learning models, likely covering techniques to validate that model routing decisions are effective and functioning a

arXiv:2606.04349v1 Announce Type: cross Abstract: Conventional Post-Training Quantization (PTQ) methods struggle with 4-bit Omni-modal Large Language Models (OLLMs) due to the extreme distribution het

arXiv:2606.04847v1 Announce Type: cross Abstract: Native GPU kernel generation turns high-level tensor programs into executable, efficient low-level code. Existing Large Language Models (LLMs) struggl

arXiv:2606.04562v1 Announce Type: new Abstract: Purpose The WHO's COVID-19 non-pharmaceutical interventions (e.g., lockdowns, vaccinations) effectively curb transmission but impose heavy economic stra

arXiv:2606.04820v1 Announce Type: cross Abstract: CutMix has become the de facto standard mixing augmentation, yet its label assignment rests on a flawed assumption: The area of the pasted patch faith

Offering a “damn, I’m truly impressed” award, for the first person or team to build a domain-general AI system that can play @baldursgate3, start to finish. Will make the prize especially sweet if you

Offering @kevinroose $100,000 bet that no domain-general AI system can do this before his book comes out. (mimicking walkthroughs doesn’t count.) Offering a “damn, I’m truly impressed” award, for the

arXiv:2603.28762v2 Announce Type: replace-cross Abstract: Modern Text-to-Image (T2I) diffusion models have achieved remarkable semantic alignment, yet they often suffer from a significant lack of vari

arXiv:2606.04092v1 Announce Type: new Abstract: Flow matching models learn to transport samples from a simple prior distribution to a complex data distribution. When prior-data pairs are coupled via o

arXiv:2601.07144v3 Announce Type: replace-cross Abstract: Ensuring fairness in matching algorithms is a key challenge in allocating scarce resources and positions. Focusing on Optimal Transport (OT),

arXiv:2606.04463v1 Announce Type: new Abstract: We present OSCAR, a precise action-conditioned video world model that generalizes across different robot embodiments and enables robot policy evaluation

arXiv:2601.15158v4 Announce Type: replace-cross Abstract: Transformers trained via Reinforcement Learning (RL) with outcome-based supervision can spontaneously develop the ability to generate intermed

arXiv:2601.07408v2 Announce Type: replace Abstract: Group Relative Policy Optimization (GRPO) has emerged as a promising critic-free reinforcement learning paradigm for reasoning tasks. However, stand

arXiv:2602.19799v2 Announce Type: replace-cross Abstract: Despite recent algorithmic advances, we still lack principled ways to leverage the well-documented rescaling symmetries in ReLU neural network

arXiv:2606.04780v1 Announce Type: new Abstract: Persistent LLM agents require memory representations that make the formation of person understanding explicit across long term interaction. Existing age

arXiv:2606.04143v1 Announce Type: cross Abstract: Accurate flood forecasting is essential for mitigating disaster risks and protecting communities. However, purely data-driven machine learning models

arXiv:2602.23214v2 Announce Type: replace Abstract: Plug-and-Play diffusion prior (PnPDP) frameworks have emerged as a powerful paradigm for solving imaging inverse problems by treating pretrained gen

arXiv:2606.04095v1 Announce Type: cross Abstract: Small open-weight models struggle at long-form creative writing: their generated stories either fall far short of the requested length, or their quali