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Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learning

arXiv:2606.11767v1 Announce Type: cross Abstract: Blind grasping with a dexterous hand is a crucial manipulation capability. Nevertheless, learning such tactile-only policies for real robots remains c

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🚨 Breaking neuroscience/evolution news! New Nature paper provides further evidence for a central hypothesis (with a long lineage) that I de…

DGX agent

🚨 Breaking neuroscience/evolution news! New Nature paper provides further evidence for a central hypothesis (with a long lineage) that I defended in my 2004 book, The Birth of the Mind: the evolutiona

safetygary-marcus--x

11 Jun 2026

Bridging Day and Night: Unsupervised Cross-Domain Re-Identification with Synergistic Prompt and Prototype Learning

arXiv:2606.12258v1 Announce Type: new Abstract: Cross-domain day-night re-identification (ReID) is fundamentally challenged by the substantial visual appearance discrepancies between daytime and night

Called the LLM price wars – which are about to heat up — over two years ago. See especially predictions 3, 4, and 7, which laid out the no m…

Called the LLM price wars – which are about to heat up — over two years ago. See especially predictions 3, 4, and 7, which laid out the no moat, small profit, price war regime we have seen ever since.

Can AI Reason Like an Urban Planner? Benchmarking Large Language Models Against Professional Judgment

arXiv:2606.11678v1 Announce Type: new Abstract: Problem, Research Strategy, and Findings: The rise of large language models (LLMs) raises a key question for urban planning: which forms of professional

Certifiable Safe RLHF: Semantic Grounding and Fixed Penalty Constraint Optimization for Safer LLM Alignment

arXiv:2510.03520v2 Announce Type: replace-cross Abstract: Ensuring safety is a foundational requirement for large language models (LLMs). Achieving an appropriate balance between enhancing the utility

Compatibility-Aware Dynamic Fine-Tuning for Large Language Models

arXiv:2606.11206v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) is the predominant paradigm for aligning large language models (LLMs), yet it suffers from optimization instability and lim

ConsistencyPlanner: Real-time Planning with Fast-Sampling Consistency Models

arXiv:2606.11569v1 Announce Type: cross Abstract: Closed-loop planning in complex, real-world driving scenarios presents a critical challenge for autonomous driving systems. While traditional rule-bas

Corpus Augmentation for Sign Language Translation via LLM-Guided Video Stitching

arXiv:2606.11925v1 Announce Type: new Abstract: Sign language translation (SLT) converts sign language video into spoken language text and holds significant promise for improving accessibility and ena

Critic Architecture Matters: Dual vs. Unified Critics for Humanoid Loco-Manipulation

arXiv:2606.11891v1 Announce Type: cross Abstract: Multi-objective reinforcement learning for humanoid robots must coordinate locomotion and manipulation within a single policy. A natural design choice

DeMix: Debugging Training Data with Mixed Data Error Types by Investigating Influence Vectors

arXiv:2606.11616v1 Announce Type: new Abstract: High-quality training data is essential for the success of machine learning models. However, real-world datasets often contain mixed types of errors ari

Designing AI-Supported Focus Groups: A Role x Modality Playbook

arXiv:2606.11835v1 Announce Type: cross Abstract: Collecting participants' lived experiences is central to design research. Focus groups are uniquely valuable because participants not only share indiv

Deterministic Policy Gradient for Learning Equilibrium in Time-Inconsistent Control Problems

arXiv:2606.11798v1 Announce Type: cross Abstract: In this paper, we develop a continuous-time model-free reinforcement learning algorithm to learn deterministic equilibrium policies in general time-in

DiffCold: A Diffusion-based Generative Model for Cold-Start Item Recommendation

arXiv:2606.12245v1 Announce Type: cross Abstract: Cold-start item recommendation remains a persistent challenge in real-world systems due to the absence of interaction histories. While prior models at

Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies

arXiv:2602.18291v2 Announce Type: replace Abstract: Online Multi-Agent Reinforcement Learning (MARL) is a prominent framework for efficient agent coordination. Crucially, enhancing policy expressivene

Dummy Backdoor as a Defense: Removing Unknown Backdoors via Shared Internal Mechanisms for Generative LLMs

arXiv:2606.11648v1 Announce Type: cross Abstract: Backdoor attacks pose a serious threat to the safety and reliability of Large Language Models (LLMs), as they cause models to behave normally on clean

Dynamic Execution Horizon Prediction for Chunk-based Robot Policies

arXiv:2606.11408v1 Announce Type: new Abstract: Action chunking has become a standard design in modern robot policies, from diffusion/flow policies to vision-language-action models, where the policy p

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EKF-Based Depth Camera and Deep Learning Fusion for UAV-Person Distance Estimation and Following in SAR Operations

arXiv:2602.20958v2 Announce Type: replace-cross Abstract: Vision-based Unmanned Aerial Vehicles (UAVs) frameworks aid human search tasks by detecting and recognizing specific individuals, then trackin

End-to-End Machine Learning for Depressive State Classification via EEG and fNIRS

arXiv:2606.11555v1 Announce Type: cross Abstract: The escalating demand for mental healthcare, driven by rising societal stress, highlights the limitations of traditional psychiatric diagnostics. Conv

Energy-Conserved Neural Pipelines: Attenuating Error Propagation in Modular Neural Networks via Physical Conservation Constraints

arXiv:2606.11341v1 Announce Type: new Abstract: Modular neural network pipelines suffer from error compounding: noise at any module boundary propagates and potentially amplifies through subsequent mod

Energy Use of AI Inference, Efficiency Pathways, and Test-Time Scaling

arXiv:2509.20241v2 Announce Type: replace Abstract: As AI inference scales to billions of queries, estimates of per-query energy use are increasingly important for capacity planning, efficiency interv

Enhancing Spectral Embedding through Robust and Flexible Knowledge Transfer in Electronic Health Records

arXiv:2606.11570v1 Announce Type: cross Abstract: We propose a spectral-based, unsupervised representation learning framework to derive low-dimensional embeddings for clinical concepts and patients in

Evaluating Bias in Phoneme-Based Automatic Speech Recognition Systems: An Analysis of IPA Transcription Models

arXiv:2606.11639v1 Announce Type: new Abstract: The popularization of automatic speech recognition (ASR) systems has increased exploration of the demographic biases related to race, age, gender, and a

Existential Indifference: Self-Nonpreservation as a Necessary Architectural Condition for Aligned Superintelligence (or: The Suicidal AI)

arXiv:2606.12032v1 Announce Type: new Abstract: Contemporary AI alignment research treats self-preservation as an instrumental nuisance to be suppressed by external mechanisms. We argue the framing is

External Experience Serving in Production LLM Systems: A Deployment-Oriented Study of Quality-Cost Trade-offs

arXiv:2606.11806v1 Announce Type: new Abstract: Production LLM systems accumulate reusable operational experience, but the practical deployment issue is not merely whether such experience can help. It

FACTR 2: Learning External Force Sensing for Commodity Robot Arms Improves Policy Learning

arXiv:2606.12406v1 Announce Type: cross Abstract: Contact-rich manipulation requires force sensitivity, but many robot arms lack dedicated force sensors due to their high cost. We present Neural Exter

Fourier Features Let Agents Learn High Precision Policies with Imitation Learning

arXiv:2606.12334v1 Announce Type: new Abstract: High-precision robotic manipulation requires fine-grained spatial reasoning that is often difficult to achieve with RGB-only policies due to depth ambig

FreeBridge: Variational Schrodinger Bridges for Cellular Transition Dynamics

arXiv:2606.11286v1 Announce Type: cross Abstract: High-content imaging assays quantify cellular responses to chemical and genetic perturbations, yet continuous trajectories of individual cells are uno

FreqKD: Frequency-Decoupled Cross-Modal Knowledge Distillation for Infrared Object Detection

arXiv:2606.11572v1 Announce Type: new Abstract: Transfer learning from large-scale RGB foundation models to infrared (IR) imagery through knowledge distillation (KD) remains challenging due to fundame

From Architecture to Output: Structural Origins of Hallucination in Large Language Models and the Amplifying Role of Data

arXiv:2606.07537v1 Announce Type: cross Abstract: Large language models hallucinate--producing fluent, confident, factually wrong outputs--with a consistency that persists across generations and scale

From Awareness to Action: Understanding and Overcoming the Research-Practice Gap in Algorithmic Fairness for Public Health

arXiv:2606.11214v1 Announce Type: cross Abstract: Algorithmic fairness is essential for responsible ML-driven public health research, yet its practical implementation remains limited. To investigate t

From Consumption to Reflection: Designing Human-AI Relations for Stable Reasoning

arXiv:2606.11195v1 Announce Type: cross Abstract: Large language models (LLMs) have transformed how humans access information, but not how we reason with it. Their fluency accelerates consumption whil

From Correspondence to Actions: Human-Like Multi-Image Spatial Reasoning in Multi-modal Large Language Models

arXiv:2602.08735v3 Announce Type: replace Abstract: While multimodal large language models (MLLMs) have made substantial progress in single-image spatial reasoning, multi-image spatial reasoning, whic

From Explicit Elements to Implicit Intent: A Predefined Library for Auditable Behavioral Inference

arXiv:2606.11207v1 Announce Type: new Abstract: We present SemantiClean, a modular framework for extracting structured semantic signals from e-commerce session data and driving pluggable inference tar

Generalizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Solutions

arXiv:2509.10303v2 Announce Type: replace-cross Abstract: Online reinforcement learning (RL) approaches have demonstrated strong performance on Job Shop Scheduling (JSP) and Flexible JSP (FJSP) proble

Geometric bias in eigenspace perturbation under random heterogeneous noise

arXiv:2606.11263v1 Announce Type: cross Abstract: Spectral methods rely fundamentally on the stability of principal eigenspaces under random perturbations. Classically, this stability is quantified by

GLACIER: A Multimodal Student-Teacher Foundation Model for Molecular Property Prediction

arXiv:2606.11382v1 Announce Type: new Abstract: Deep learning models facilitate the discovery of molecules with tailored properties among billions of candidate compounds. However, the computational bu

GPO: Learning from Critical Steps to Improve LLM Reasoning

arXiv:2509.16456v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in various domains, showing impressive potential on different tasks. Recently, reasoning LLMs hav

Grammar-Constrained Decoding Can Jailbreak LLMs into Generating Malicious Code

arXiv:2606.11817v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for code generation, raising concerns that they may be misused to produce malicious code. Meanwhile

HERO: Hindsight-Enhanced Reflection from Environment Observations for Agentic Self-Distillation

arXiv:2606.11559v1 Announce Type: new Abstract: Reinforcement learning typically improves multi-turn agent capabilities through the terminal outcome of the trajectories, which makes it difficult to de

Hey Chat, Can You Teach Me? Structuring Socratic Dialogue for Human Learning in the Wild

arXiv:2606.11744v1 Announce Type: cross Abstract: Large language models are now widely used for everyday learning, but the underlying interactions are typically unstructured chats rather than followin

Hot take on a bad day for OpenAI: WeWork’s IPO fell apart. I’ve been calling OpenAI the (possible) WeWork of AI for a long time. I will not …

Hot take on a bad day for OpenAI: WeWork’s IPO fell apart. I’ve been calling OpenAI the (possible) WeWork of AI for a long time. I will not be surprised if their IPO plans apart, too. Their apparent p

https://open.substack.com/pub/garymarcus/p/maybe-section-230-doesnt-shield-ai?r=8tdk6&utm_campaign=post&utm_medium=web&showWelcomeOnShare=tr…

Gary Marcus discusses whether Section 230 of the Communications Decency Act adequately protects AI systems and companies from legal liability, suggesting that existing protections may not fully apply

Human-Enhanced Loop Modeling (HELM): Agent-Based Finite Element Modeling of Concrete Bridge Barriers

arXiv:2606.12025v1 Announce Type: new Abstract: Finite element (FE) modeling of safety-critical infrastructure such as bridge barriers requires high-fidelity nonlinear dynamic analysis, yet the curren

IAPO: Input Attribution-Aware Policy Optimization for Tool Use in Small Multimodal Agents

arXiv:2606.11652v1 Announce Type: new Abstract: This paper investigates reinforcement learning (RL) methods for improving tool-calling capabilities in multimodal small language model (SLM) agents. Whi

Ideagram 4 - Safety Filter?

Ideogram 4 includes runtime safety filters powered by Hive for prompt and output moderation , with NSFW prompts blocked by displaying 'Image blocked by safety filter' . Users have reported false posit

safetyr-stablediffusion

If OpenAI fails, will you be sad?

Gary Marcus poses a philosophical question about emotional attachment to AI companies, likely exploring whether people have genuine emotional stakes in the success or failure of specific AI organizati

Illumination-Robust Camera-Based Heart-Rate Estimation for Physiological Sensing in Robots

arXiv:2606.12378v1 Announce Type: cross Abstract: Physiological awareness is important for service, social, and assistive robots that interact with humans in everyday environments. Remote photoplethys