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GARL: Game-Theoretic Reinforcement Learning for Multi-Agent Strategic Prioritisation

arXiv:2606.05002v1 Announce Type: new Abstract: LLM-based multi-agent systems are increasingly used for strategic decision-making tasks. In such settings, performance depends not only on individual mo

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Generalizable Multi-Task Learning for Wireless Networks Using Prompt Decision Transformers

DGX agent

arXiv:2606.04328v1 Announce Type: cross Abstract: Future wireless networks demand rapid adaptation to highly heterogeneous environments and dynamic task configurations, necessitating a shift from conv

safetyarxiv-cs-ai

4 Jun 2026

Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

arXiv:2606.05015v1 Announce Type: new Abstract: World models, learned generative models that predict how an environment evolves, have become a promising tool for sample-efficient robot learning. Yet h

Geometry-Aware Distillation for Prompt Tuning Biomedical Vision-Language Models

arXiv:2606.04922v1 Announce Type: cross Abstract: Current prompt-based and adapter-based tuning of vision-language models (VLMs) is attractive for medical imaging, where clinical data sensitivity favo

Geospatial Foundation Models to Enable Progress on Sustainable Development Goals

arXiv:2505.24528v3 Announce Type: replace Abstract: Foundation Models (FMs) are large-scale, pre-trained artificial intelligence (AI) systems that have revolutionized natural language processing and c

safetyarxiv-cs-cv

Global Sketch-Based Watermarking for Diffusion Language Models

arXiv:2606.04486v1 Announce Type: cross Abstract: Watermarking methods for language models have been studied extensively in the autoregressive setting, where tokens are generated sequentially. These w

Good Reasoning Makes Good Demonstrations: Implicit Reasoning Quality Supervision via In-Context Reinforcement Learning

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

GRAIL: Gradient-Reweighted Advantages for Reinforcement Learning with Verifiable Rewards

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

HapTile: A Haptic-Informed Vision-Tactile-Language-Action Dataset for Contact-Rich Imitation Learning

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 …

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

Hybrid Adversarial Defence for Natural Language Understanding Tasks

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 c…

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 billi…

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

If you could buy into exactly one of the three mega IPOs, which would it be?

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

if you had 100k to invest in OpenAI and/or Anthropic IPOs which would you go for?

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 lea…

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

Imbuing Large Language Models with Bidirectional Logic for Robust Chain Repair

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

In-Context Graphical Inference

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 🤦‍♂️

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

Inference-Time Vulnerability Beyond Shallow Safety: Alignment Along Generation Trajectories

arXiv:2606.04778v1 Announce Type: new Abstract: Safety-aligned Large Language Models (LLMs) remain vulnerable to interventions during inference that redirect generation toward harmful outputs. Recent

Instance-Level Post Hoc Uncertainty Quantification in Object Detection

arXiv:2606.04656v1 Announce Type: cross Abstract: Object detection is a safety-critical component of autonomous driving. It is essential to quantify the uncertainty in bounding-box predictions for saf

Instant-Fold: In-Context Imitation Learning for Deformable Object Manipulation

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

Inverse Critical Experiment Design via Gradient Optimization and a Multigroup Attention-Based Neural Network Architecture

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

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

it takes balls to offer an IPO on a trillion dollar valuation when you are just months from bankruptcy. but maybe that’s what is happening. …

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 p…

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

KODA: Contrastive Representation Comparison and Alignment for Vision-Language Foundation Models

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 confianc…

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

safetyyoshua-bengio--x

Large Language Models in K-12 Education: Alignment with State Curriculum Standards and Student Personas

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

LaVIDE: Language-Prompted Satellite Change Detection via Map-Image Alignment

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

Learning Empirically Admissible Neural Heuristics for Combinatorial Search

arXiv:2606.04860v1 Announce Type: cross Abstract: Finding optimal solution paths for combinatorial puzzles like the Rubik's Cube, sliding tile puzzles, and Lights Out remains a classical challenge in

Learning While Acting: A Skill-Enhanced Test-Time Co-Evolution Framework for Online Lifelong Learning Agents

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

Listening to the Workforce: Measuring Construction Worker Safety Attitudes from Social Media Discourse Using LLMs

arXiv:2606.04450v1 Announce Type: new Abstract: Worker safety attitudes are key determinants of whether protective practices are applied or bypassed on construction sites. Yet measuring them at scale

M3imic: Learning a Versatile Whole-Body Controller for Multimodal Motion Mimicking

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

MaskForge: Structure-Aware Adaptive Attacks for Jailbreaking Diffusion Large Language Models

arXiv:2606.04027v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by iteratively denoising partially masked sequences under bidirectional context, exposing a safe

MATCH: Multi-faceted Adaptive Topo-Consistency for Semi-Supervised Histopathology Segmentation

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

safetyarxiv-cs-cv

Measuring Model Robustness via Fisher Information: Spectral Bounds, Theoretical Guarantees, and Practical Algorithms

arXiv:2606.04767v1 Announce Type: cross Abstract: The robustness of deep neural networks is crucial for safety-critical deployments, yet existing evaluation methods are often attack-dependent and lack

safetyarxiv-cs-cv

MENTOR: A Metacognition-Driven Self-Evolution Framework for Uncovering and Mitigating Implicit Domain Risks in LLMs

arXiv:2511.07107v3 Announce Type: replace Abstract: Ensuring the safety of Large Language Models (LLMs) is critical for real-world deployment. However, current safety measures often fail to address im

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

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

safetytechmeme

(Mis)generalization of Helpful-only Fine-tuning

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

MM-BizRAG: Rethinking Multimodal Retrieval-Augmented Generation for General Purpose Enterprise Q&A

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

Model Evaluations: Prove Your Routing Policy Actually Works

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

safetydigitalocean

MorphoQuant: Modality-Aware Quantization for Omni-modal Large Language Models

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

Multi-Agent Next-Best-View Optimization for Risk-Averse Planning

arXiv:2606.04158v1 Announce Type: new Abstract: Multi-agent Next-Best-View (NBV) selection for safe path planning in uncertain and unknown environments requires informative, safety-aware, and efficien

MusaCoder: Native GPU Kernel Generation with Full-Stack Training on Moore Threads GPU

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

Neetyabhas: A Framework for Uncertainty-Aware Public Policy Optimization in Rational Agent-Based Models

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

OA-CutMix: Correcting the Label Bias of CutMix

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

Off-Distribution Voices: Fanfiction Subgenres as Universal Vernacular Jailbreaks for Aligned LLMs

arXiv:2606.04483v1 Announce Type: new Abstract: Existing jailbreaks against aligned LLMs are discrete artifacts whose surface forms are easy to fingerprint and patch. We argue that the real failure mo