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The NY State legislature passes a one-year moratorium on new large data centers, the first statewide ban of its kind if Governor Kathy Hochul signs it into law (Lauren Feiner/The Verge)

Lauren Feiner / The Verge: The NY State legislature passes a one-year moratorium on new large data centers, the first statewide ban of its kind if Governor Kathy Hochul signs it into law — It could b

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Toward Culturally Aligned LLMs through Ontology-Guided Multi-Agent Reasoning

arXiv:2601.21700v3 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly support culturally sensitive decision making, yet often exhibit misalignment due to skewed pretraining dat

Towards a Data Flywheel for Embodied Intelligence in Logistics

arXiv:2606.05960v1 Announce Type: new Abstract: Embodied intelligence is moving from laboratory demonstrations toward industrial deployment, with the logistics industry serving as a key application sc

safetyarxiv-cs-ro

Two-Way Is Better Than One: Bidirectional Alignment with Cycle Consistency for Exemplar-Free Class-Incremental Learning

arXiv:2606.05675v1 Announce Type: cross Abstract: Continual learning (CL) seeks models that acquire new skills without erasing prior knowledge. In exemplar-free class-incremental learning (EFCIL), thi

UNIVID: Unified Vision-Language Model for Video Moderation

arXiv:2606.05748v1 Announce Type: cross Abstract: Global-scale video moderation faces a dual challenge: the need for fine-grained multi-modal reasoning and the demand for interpretable outputs to supp

Unpaired RGB-Thermal Gaussian-Splatting Using Visual Geometric Transformers

arXiv:2606.05491v1 Announce Type: new Abstract: Multi-modal novel view synthesis (NVS) combining RGB and thermal imagery enables precise 3D scene reconstruction with visual and thermal information. Ho

Unveiling the Unknown: Open Vocabulary Object Detection with Scene Graphs

arXiv:2606.05916v1 Announce Type: new Abstract: Open-vocabulary object detection seeks to identify novel object categories that were not part of the training data. Many knowledge distillation-based ap

Using street view images and visual LLMs to predict heritage values for governance support: Risks, ethics, and policy implications

arXiv:2601.06056v2 Announce Type: replace-cross Abstract: During 2025 and 2026, the Energy Performance of Buildings Directive is being implemented in the European Union member states, requiring all me

Value-and-Structure Alignment for Routing-Consistent Quantization of Mixture-of-Experts Models

arXiv:2606.05688v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models scale foundation models efficiently by activating only a subset of experts for each token, but their large number of exp

ViCuR: Visual Cues as Recoverable Privilege for Multimodal On-Policy Distillation

arXiv:2606.05718v1 Announce Type: new Abstract: On-policy distillation (OPD) improves reasoning by training a student on trajectories sampled from its own policy under supervision from a teacher. In m

VOLD: Reasoning Transfer from LLMs to Vision-Language Models via On-Policy Distillation

arXiv:2510.23497v3 Announce Type: replace Abstract: Training vision-language models (VLMs) for complex reasoning remains a challenging task, i.a. due to the scarcity of high-quality image-text reasoni

VOLT: Vision and Language Trajectory Segmentation for Faster-than-Demonstration Policies

arXiv:2606.06323v1 Announce Type: new Abstract: Humans often take longer to demonstrate a task than a robot would need to execute it. Rather than learning to replicate the demonstration at the same pa

safetyarxiv-cs-ro

What's in a Name? Morphological Shortcuts by LLMs in Pharmacology

arXiv:2606.05616v1 Announce Type: new Abstract: The morphological form of a word can often give cues to its meaning, but purely relying on these mappings can lead to overgeneralization in high-stakes

When AI Says It Feels

arXiv:2606.05734v1 Announce Type: cross Abstract: Large language models (LLMs) are generally constrained from expressing feelings through human-preference alignment in post-training processes. This po

When Evidence is Sparse: Weakly Supervised Early Failure Alerting in Dialogs and LLM-Agent Trajectories

arXiv:2606.05414v1 Announce Type: new Abstract: Early failure alerting requires deciding, while a dialog or agent trajectory is still unfolding, whether to flag it as likely to fail. This is challengi

worth 2 trillion, easily. maybe more!

Gary Marcus posted on X/Twitter expressing his assessment that something (likely an AI system, company, or technology) could be worth $2 trillion or more, suggesting significant potential value. Witho

WOW!!!! 👏 Great news for anyone who didn’t want to be fast-tracked into this madness. SpaceX now needs to stand on its own two feet.

WOW!!!! 👏 Great news for anyone who didn’t want to be fast-tracked into this madness. SpaceX now needs to stand on its own two feet. Wow, the S&P Dow Jones Indices has just officially announced that t

Wow…this is a tell people. There is no path to profitability. They need to socialize losses.

Wow…this is a tell people. There is no path to profitability. They need to socialize losses. Trump administration, OpenAI discussing possible government stake in the AI startup https://www.cnbc.com/20

3PoinTr: 3D Point Tracks for Learning Manipulation from Unconstrained Human Videos

arXiv:2603.08485v2 Announce Type: replace Abstract: Learning manipulation policies from human videos could greatly reduce the need for expensive robot demonstrations, but existing approaches typically

safetyarxiv-cs-ro

A brief history of claims about AI and employment 2016: Hinton said radiologists would soon be replaced; they weren’t. He was hyping his tec…

A brief history of claims about AI and employment 2016: Hinton said radiologists would soon be replaced; they weren’t. He was hyping his tech, not basing it on careful analysis of the industry. 2026:

A Goal-Set Characterization of Task Composition in the Boolean Task Algebra

arXiv:2606.04053v1 Announce Type: cross Abstract: The Boolean Task Algebra (BTA) provides a principled framework for zero-shot task composition in reinforcement learning by equipping goal-reaching tas

A Pathology Foundation Model for Gastric Cancer with Real-World Validation

arXiv:2606.04792v1 Announce Type: new Abstract: Gastric cancer remains a major cause of cancer mortality, yet its histological and molecular heterogeneity complicates diagnosis and risk stratification

A team of about 3 from @ControlAI cold-emailed the UK Parliament about AI extinction risk. At the time they had no contacts, insider help, o…

A team of about 3 from @ControlAI cold-emailed the UK Parliament about AI extinction risk. At the time they had no contacts, insider help, or established organisation behind them. 16 months later: 125

safetyconnor-leahy--x

A Unified Framework for Locality in Scalable MARL

arXiv:2602.16966v2 Announce Type: replace-cross Abstract: Scalable methods for networked multi-agent reinforcement learning let each agent plan using only a small neighborhood of the agent graph. This

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks

arXiv:2510.24342v2 Announce Type: replace Abstract: Prior brain-AI alignment studies are typically constrained by specific inputs and tasks, limiting their ability to capture organizational properties

Achieving Rotation-Invariant Convolution via Non-Learnable Orientation Alignment Operators

arXiv:2404.11309v2 Announce Type: replace Abstract: Achieving rotational invariance in deep neural networks without data augmentation is a research hotspot. Intrinsic invariance enables features to ca

Activation Steering of Video Generation Models via Reduced-Order Linear Optimal Control

arXiv:2606.04775v1 Announce Type: cross Abstract: Text-to-video (T2V) models trained on large-scale web data can generate undesired content, motivating interventions that reduce harmful outputs withou

Adaptive Calibration for Fair and Performant Facial Recognition

arXiv:2606.04469v1 Announce Type: cross Abstract: We introduce Adaptive Calibration (AC), a novel calibration strategy for facial recognition that maps cosine similarity between normalized embeddings

Adaptive Information Control for Search-Augmented LLM Reasoning

arXiv:2602.01672v2 Announce Type: replace Abstract: Search-augmented reasoning agents interleave multi-step reasoning with external retrieval, but uncontrolled retrieval can introduce redundant eviden

AI enthusiasts are in a race against time, AI skeptics are in a race against entropy

AI enthusiasts are in a race against time, AI skeptics are in a race against entropy Charity Majors neatly captures the dynamic between AI enthusiasts and AI skeptics, both of whom are trying to build

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Anycast Performance in Context

arXiv:2606.04298v1 Announce Type: cross Abstract: IP anycast lets a service advertise one address from many physical sites, leaving BGP to map each client to a site. It is central to the DNS root serv

Be Fair! Can Machine Learning Engineering Agents Adhere to Fairness Constraints?

arXiv:2606.04971v1 Announce Type: new Abstract: Machine learning engineering (MLE) agents promise to automate end-to-end ML pipeline development from raw data and natural language instructions, potent

Beyond Static Priors: Dynamic Neural Guidance for Large-Scale Ant Colony Optimization

arXiv:2606.04039v1 Announce Type: cross Abstract: Neural-guided Ant Colony Optimization (ACO) suffers from a fundamental training-inference misalignment: policies are typically trained to generate sta

Beyond Symmetric Alignment: Spectral Diagnostics of Modality Imbalance in Vision-Language Models in the Medical Domain

arXiv:2606.04613v1 Announce Type: new Abstract: Vision-Language Models (VLMs) struggle when applied to medical image-text data, yet the tools available to diagnose this failure remain limited. Existin

BiasGRPO: Stabilizing Bias Mitigation in High-Variance Reward Landscapes via Group-Relative Policy Optimization

arXiv:2606.04807v1 Announce Type: new Abstract: Mitigating social bias in Large Language Models (LLMs) presents a distinct alignment challenge: unlike verifiable tasks, bias lacks a single ground trut

Blessing from Human-AI Interaction: Super Reinforcement Learning in Confounded Environments

arXiv:2209.15448v3 Announce Type: replace Abstract: As AI becomes more prevalent throughout society, effective methods of integrating humans and AI systems that leverage their respective strengths and

Causal Multi-fidelity Surrogate Forward and Inverse Models for ICF Implosions

arXiv:2509.05510v3 Announce Type: replace-cross Abstract: Continued progress in inertial confinement fusion (ICF) requires solving inverse problems relating experimental observations to simulation inp

Certified Neural Approximations of Nonlinear Dynamics

arXiv:2505.15497v3 Announce Type: replace Abstract: Neural networks hold great potential to act as approximate models of nonlinear dynamical systems, with the resulting neural approximations enabling

Channel-Oriented Design for EEG-to-Music Reconstruction

arXiv:2606.04040v1 Announce Type: cross Abstract: Brain-computer interfaces aim to decode naturalistic stimuli from neural signals, yet most progress to date has focused on vision and language. In thi

Confidence Before Answering: A Paradigm Shift for Efficient LLM Uncertainty Estimation

arXiv:2603.05881v2 Announce Type: replace Abstract: Reliable deployment of large language models (LLMs) requires accurate uncertainty estimation. Existing methods are predominantly answer-first, produ

COP-Q: Safety-First Reinforcement Learning for Robot Control via Cholesky-Ordered Projection

arXiv:2606.04749v1 Announce Type: cross Abstract: Safe robot control requires maximizing return while satisfying safety constraints. In off-policy safe reinforcement learning, reward and safety Q-valu

CoRe-MoE: Contrastive Reweighted Mixture of Experts for Multi-Terrain Humanoid Locomotion with Gait Adaptation

arXiv:2606.04718v1 Announce Type: cross Abstract: Humans primarily rely on walking and running to traverse complex terrains, without resorting to unnecessarily complex motion patterns. Similarly, huma

Covert Influence Between Language Models

arXiv:2606.04071v1 Announce Type: cross Abstract: As language models increasingly consume one another's outputs, covert influence -- a phenomenon where a sender's payload (the behavioral disposition i

Crafting Your Evolving Dreams: Concept-Incremental Versatile Customization

arXiv:2606.04797v1 Announce Type: new Abstract: Custom diffusion models (CDMs) have garnered significant interest owing to their remarkable capacity for generating personalized concepts. However, the

Culturally Grounded Personas in Large Language Models: Characterization and Alignment with Socio-Psychological Value Frameworks

arXiv:2601.22396v2 Announce Type: replace-cross Abstract: Despite the growing utility of Large Language Models (LLMs) for simulating human behavior, the extent to which these synthetic personas accura

Customizing the Inductive Biases of Softmax Attention using Structured Matrices

arXiv:2509.07963v2 Announce Type: replace Abstract: The core component of attention is the scoring function, which transforms the inputs into low-dimensional queries and keys and takes the dot product

death of tokenmaxxing = potentially a very serious issue for all three big IPOs.

death of tokenmaxxing = potentially a very serious issue for all three big IPOs. 🚨 Sam Altman warns OpenAi and Anthropic are experiencing severe pullback on Ai spending as companies put significant re

DiffAero: A GPU-Accelerated Differentiable Simulation Framework for Efficient Quadrotor Policy Learning

arXiv:2509.10247v1 Announce Type: cross Abstract: This letter introduces DiffAero, a lightweight, GPU-accelerated, and fully differentiable simulation framework designed for efficient quadrotor contro