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Grasp as You Dream: Imitating Functional Grasping from Generated Human Demonstrations

arXiv:2604.07517v1 Announce Type: new Abstract: Building generalist robots capable of performing functional grasping in everyday, open-world environments remains a significant challenge due to the vas

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Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs

DGX agent

arXiv:2604.07655v1 Announce Type: cross Abstract: Hard-gated safety checkers often over-refuse and misalign with a vendor's model spec; prevailing taxonomies also neglect robustness and honesty, yield

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10 Apr 2026

Guiding a Diffusion Model by Swapping Its Tokens

arXiv:2604.08048v1 Announce Type: new Abstract: Classifier-Free Guidance (CFG) is a widely used inference-time technique to boost the image quality of diffusion models. Yet, its reliance on text condi

Harnessing Embodied Agents: Runtime Governance for Policy-Constrained Execution

arXiv:2604.07833v1 Announce Type: new Abstract: Embodied agents are evolving from passive reasoning systems into active executors that interact with tools, robots, and physical environments. Once gran

Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization

arXiv:2604.06285v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have become essential for tasks such as image synthesis, captioning, and retrieval by aligning textual and visual inform

How Independent are Large Language Models? A Statistical Framework for Auditing Behavioral Entanglement and Reweighting Verifier Ensembles

arXiv:2604.07650v1 Announce Type: cross Abstract: The rapid growth of the large language model (LLM) ecosystem raises a critical question: are seemingly diverse models truly independent? Shared pretra

How Psychological Learning Paradigms Shaped and Constrained Artificial Intelligence

arXiv:2603.18203v3 Announce Type: replace Abstract: Current artificial intelligence systems struggle with systematic compositional reasoning: the capacity to recombine known components in novel config

How to Evaluate Speech Translation with Source-Aware Neural MT Metrics

arXiv:2511.03295v3 Announce Type: replace-cross Abstract: Automatic evaluation of ST systems is typically performed by comparing translation hypotheses with one or more reference translations. While e

HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns

arXiv:2601.10198v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona s

I agree totally @Gary. I’ve been saying this since the ChatGPT moment in Nov 22. Thank you for saying it out loud @demishassabis. Too much t…

I agree totally @Gary. I’ve been saying this since the ChatGPT moment in Nov 22. Thank you for saying it out loud @demishassabis. Too much time and energy being spent on mitigating the unintended cons

I rest my case: Mythos isn’t AGI. It’s not even better at biology than the last model. It’s tuned to particular things, not a giant advance …

I rest my case: Mythos isn’t AGI. It’s not even better at biology than the last model. It’s tuned to particular things, not a giant advance towards general intelligence. Same as it ever was. @GaryMarc

Improving Semantic Uncertainty Quantification in Language Model Question-Answering via Token-Level Temperature Scaling

arXiv:2604.07172v1 Announce Type: new Abstract: Calibration is central to reliable semantic uncertainty quantification, yet prior work has largely focused on discrimination, neglecting calibration. As

Incorporating Social Awareness into Control of Unknown Multi-Agent Systems: A Real-Time Spatiotemporal Tubes Approach

arXiv:2510.25597v2 Announce Type: replace-cross Abstract: This paper presents a decentralized control framework that incorporates social awareness into multi-agent systems with unknown dynamics to ach

Incremental Residual Reinforcement Learning Toward Real-World Learning for Social Navigation

arXiv:2604.07945v1 Announce Type: new Abstract: As the demand for mobile robots continues to increase, social navigation has emerged as a critical task, driving active research into deep reinforcement

Indeed, if the LLM crew would just stick to this narrative, I would have a lot less to say 🤷‍♂️

Indeed, if the LLM crew would just stick to this narrative, I would have a *lot* less to say 🤷‍♂️ @GaryMarcus All we want is truth. Instead of overhyping LLMs, they should keep narative: -LLMs are use

Inside-Out: Measuring Generalization in Vision Transformers Through Inner Workings

arXiv:2604.08192v1 Announce Type: cross Abstract: Reliable generalization metrics are fundamental to the evaluation of machine learning models. Especially in high-stakes applications where labeled tar

Invisible to Humans, Triggered by Agents: Stealthy Jailbreak Attacks on Mobile Vision-Language Agents

arXiv:2510.07809v4 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) empower autonomous mobile agents, yet their security under realistic mobile deployment constraints remain

Just launched at @aiDotEngineer : our official AGI Pills! prescribe one (1) if your colleague is saying we are hitting a wall and/or trying …

Just launched at @aiDotEngineer : our official AGI Pills! prescribe one (1) if your colleague is saying we are hitting a wall and/or trying to add inductive bias instead of Trusting The Model Media bt

safetyswyx--x

Karma Mechanisms for Decentralised, Cooperative Multi Agent Path Finding

arXiv:2604.07970v1 Announce Type: cross Abstract: Multi-Agent Path Finding (MAPF) is a fundamental coordination problem in large-scale robotic and cyber-physical systems, where multiple agents must co

KD-MARL: Resource-Aware Knowledge Distillation in Multi-Agent Reinforcement Learning

arXiv:2604.06691v1 Announce Type: new Abstract: Real world deployment of multi agent reinforcement learning MARL systems is fundamentally constrained by limited compute memory and inference time. Whil

LangDriveCTRL: Natural Language Controllable Driving Scene Editing with Multi-modal Agents

arXiv:2512.17445v2 Announce Type: replace Abstract: LangDriveCTRL is a natural-language-controllable framework for editing real-world driving videos to synthesize diverse traffic scenarios. It represe

Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning

arXiv:2604.07941v1 Announce Type: new Abstract: Post-training has become central to turning pretrained large language models (LLMs) into aligned and deployable systems. Recent progress spans supervise

Learning to Negotiate: Multi-Agent Deliberation for Collective Value Alignment in LLMs

arXiv:2603.10476v2 Announce Type: replace Abstract: LLM alignment has progressed in single-agent settings through paradigms such as RL with human feedback (RLHF), while recent work explores scalable a

Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM

arXiv:2604.08425v1 Announce Type: cross Abstract: When humans label subjective content, they disagree, and that disagreement is not noise. It reflects genuine differences in perspective shaped by anno

Learning Without Losing Identity: Capability Evolution for Embodied Agents

arXiv:2604.07799v1 Announce Type: new Abstract: Embodied agents are expected to operate persistently in dynamic physical environments, continuously acquiring new capabilities over time. Existing appro

Leveraging Wireless Sensor Networks for Real-Time Monitoring and Control of Industrial Environments

arXiv:2510.13820v3 Announce Type: replace-cross Abstract: This research proposes an extensive technique for monitoring and controlling the industrial parameters using Internet of Things (IoT) technolo

Limits of Difficulty Scaling: Hard Samples Yield Diminishing Returns in GRPO-Tuned SLMs

arXiv:2604.06298v1 Announce Type: new Abstract: Recent alignment work on Large Language Models (LLMs) suggests preference optimization can improve reasoning by shifting probability mass toward better

LINE: LLM-based Iterative Neuron Explanations for Vision Models

arXiv:2604.08039v1 Announce Type: new Abstract: Interpreting the concepts encoded by individual neurons in deep neural networks is a crucial step towards understanding their complex decision-making pr

LLM-based Schema-Guided Extraction and Validation of Missing-Person Intelligence from Heterogeneous Data Sources

arXiv:2604.06571v1 Announce Type: cross Abstract: Missing-person and child-safety investigations rely on heterogeneous case documents, including structured forms, bulletin-style posters, and narrative

LUMINA: Foundation Models for Topology Transferable ACOPF

arXiv:2603.04300v2 Announce Type: replace Abstract: Foundation models in general promise to accelerate scientific computation by learning reusable representations across problem instances, yet constra

Machine Unlearning in the Era of Quantum Machine Learning: An Empirical Study

arXiv:2512.19253v4 Announce Type: replace-cross Abstract: We present the first empirical study of machine unlearning (MU) in hybrid quantum-classical neural networks. While MU has been extensively exp

Mark “Metaverse” Zuckerberg totally bought Moltbook at the peak of the market 🤣

Meta acquired Moltbook, an AI-only social network launched in January 2026 by entrepreneurs Matt Schlicht and Ben Parr, after the platform had gone viral and then faded in popularity. Moltbook is ...

MCLR: Improving Conditional Modeling via Inter-Class Likelihood-Ratio Maximization and Unifying Classifier-Free Guidance with Alignment Objectives

arXiv:2603.22364v2 Announce Type: replace-cross Abstract: Diffusion models have achieved state-of-the-art performance in generative modeling, but their success often relies heavily on classifier-free

MDP modeling for multi-stage stochastic programs

arXiv:2509.22981v2 Announce Type: replace Abstract: We study a class of multi-stage stochastic programs, which incorporate modeling features from Markov decision processes (MDPs). This class includes

MedVR: Annotation-Free Medical Visual Reasoning via Agentic Reinforcement Learning

arXiv:2604.08203v1 Announce Type: new Abstract: Medical Vision-Language Models (VLMs) hold immense promise for complex clinical tasks, but their reasoning capabilities are often constrained by text-on

MemReader: From Passive to Active Extraction for Long-Term Agent Memory

arXiv:2604.07877v1 Announce Type: new Abstract: Long-term memory is fundamental for personalized and autonomous agents, yet populating it remains a bottleneck. Existing systems treat memory extraction

Mixture Proportion Estimation and Weakly-supervised Kernel Test for Conditional Independence

arXiv:2604.07191v1 Announce Type: cross Abstract: Mixture proportion estimation (MPE) aims to estimate class priors from unlabeled data. This task is a critical component in weakly supervised learning

MO-RiskVAE: A Multi-Omics Variational Autoencoder for Survival Risk Modeling in Multiple MyelomaMO-RiskVAE

arXiv:2604.06267v1 Announce Type: cross Abstract: Multimodal variational autoencoders (VAEs) have emerged as a powerful framework for survival risk modeling in multiple myeloma by integrating heteroge

MonoUNet: A Robust Tiny Neural Network for Automated Knee Cartilage Segmentation on Point-of-Care Ultrasound Devices

arXiv:2604.07780v1 Announce Type: cross Abstract: Objective: To develop a robust and compact deep learning model for automated knee cartilage segmentation on point-of-care ultrasound (POCUS) devices.

MorphDistill: Distilling Unified Morphological Knowledge from Pathology Foundation Models for Colorectal Cancer Survival Prediction

arXiv:2604.06390v1 Announce Type: cross Abstract: Background: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. Accurate survival prediction is essential for treat

MotionScape: A Large-Scale Real-World Highly Dynamic UAV Video Dataset for World Models

arXiv:2604.07991v1 Announce Type: new Abstract: Recent advances in world models have demonstrated strong capabilities in simulating physical reality, making them an increasingly important foundation f

MSCT: Differential Cross-Modal Attention for Deepfake Detection

arXiv:2604.07741v1 Announce Type: new Abstract: Audio-visual deepfake detection typically employs a complementary multi-modal model to check the forgery traces in the video. These methods primarily ex

Multi-agent Reach-avoid MDP via Potential Games and Low-rank Policy Structure

arXiv:2410.17690v2 Announce Type: replace-cross Abstract: We optimize finite horizon multi-agent reach-avoid Markov decision process (MDP) via local feedback policies. The global feedback polic

Multi-Faceted Self-Consistent Preference Alignment for Query Rewriting in Conversational Search

arXiv:2604.06771v1 Announce Type: cross Abstract: Conversational Query Rewriting (CQR) aims to rewrite ambiguous queries to achieve more efficient conversational search. Early studies have predominant

Multi-Turn Reasoning LLMs for Task Offloading in Mobile Edge Computing

arXiv:2604.07148v1 Announce Type: new Abstract: Emerging computation-intensive applications impose stringent latency requirements on resource-constrained mobile devices. Mobile Edge Computing (MEC) ad

Neural Computers

arXiv:2604.06425v1 Announce Type: cross Abstract: We propose a new frontier: Neural Computers (NCs) -- an emerging machine form that unifies computation, memory, and I/O in a learned runtime state. Un

On the Global Photometric Alignment for Low-Level Vision

arXiv:2604.08172v1 Announce Type: new Abstract: Supervised low-level vision models rely on pixel-wise losses against paired references, yet paired training sets exhibit per-pair photometric inconsiste

OpenVLThinkerV2: A Generalist Multimodal Reasoning Model for Multi-domain Visual Tasks

arXiv:2604.08539v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) has emerged as the de facto Reinforcement Learning (RL) objective driving recent advancements in Multimodal