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arXiv:2609.06444v1 Announce Type: cross Abstract: An LLM judge evaluates outputs at scale. Experts should label only where it is least sure. Its natural escalation signal conflates two uncertainties:

tutorialsarxiv-cs-lg

Decomposition-Guided Diffusion Language Models for Inertial Confinement Fusion Prediction

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DGX agent

arXiv:2609.07756v1 Announce Type: new Abstract: Inertial confinement fusion (ICF) is a leading pathway toward clean energy, but each shot at the National Ignition Facility costs on the order of one mi

model-releasesarxiv-cs-lg

9 Sept 2026

Deep Active Inference with Diffusion Policy and Multiple Timescale World Model for Real-World Exploration and Navigation

arXiv:2510.23258v2 Announce Type: replace-cross Abstract: Autonomous robotic navigation in real-world environments requires exploration to acquire environmental information as well as goal-directed na

Deep Barycentric Regression for Optimal Transport Map Estimation and its Statistical Optimality

arXiv:2609.06598v1 Announce Type: new Abstract: The optimal transport (OT) map provides a geometric transformation for aligning probability distributions and has become a useful tool in machine learni

Deep belief networks are exact

arXiv:2609.05572v1 Announce Type: cross Abstract: We prove that every strictly positive probability distribution on ({-1,1}^n) is represented exactly by a sigmoid belief network with finite parameters

Deep Learning Approach to Bearing and Induction Motor Fault Diagnosis via Data Fusion

arXiv:2506.11032v2 Announce Type: replace Abstract: Convolutional Neural Networks (CNNs) are used to evaluate accelerometer and microphone data for bearing and induction motor diagnosis. A Long Short-

Deep Learning for Biopsy-Free Subtyping of Basal Cell Carcinoma from Dermatoscopic Images

arXiv:2609.07180v1 Announce Type: new Abstract: Basal Cell Carcinoma (BCC) is the most common type of skin cancer, accounting for nearly 80% of skin cancer di- agnoses. Its optimal clinical management

Deep learning from the crowd Fundamentals of morphological galaxy classification

arXiv:2609.06316v1 Announce Type: cross Abstract: Aims. The objective of this work is to adapt a deep neural network model to perform galaxy morphological classification trained from crowd annotations

Deep Learning to Automate Parameter Extraction and Model Fitting of Two-Dimensional Transistors

model-releasesarxiv-cs-lg

arXiv:2507.05134v2 Announce Type: replace Abstract: We present a deep learning approach to extract physical parameters (e.g., mobility, Schottky contact barrier height, defect profiles) of two-dimensi

DeepSeek-V4-Flash-Vision-Exp (285B MoE) on 10-12x RTX 3090 — spec decoding, vision

model-releasesr-localllama

Running the full deepseek-ai/DeepSeek-V4-Flash-Vision-Exp on consumer Ampere — 10-12x RTX 3090, SM86-compatible vLLM build. 285B MoE, FP4 experts + FP8 attention, 157 GB weights. Highlights: - **60+ t

Denoising Models Develop Human-Like Perceptual Illusion Representations Across Architectures

arXiv:2607.17138v2 Announce Type: replace Abstract: Deep neural networks trained on natural images are shown to produce outputs consistent with human observers for brightness illusions. While this phe

Hardware

Dense Structural Compression of Transformers via Gauge-Correct Channel Removal

arXiv:2609.07264v1 Announce Type: new Abstract: Inference energy per token drives the cost and carbon footprint of deployed transformers. It is dominated by dense matrix products that incur fused mult

hardwarearxiv-cs-lg

Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM

model-releasesaws-ml-blog

Learn how to deploy Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter open-weight model, on Amazon SageMaker HyperPod with vLLM. This walkthrough covers cluster provisioning, NVFP4 quantization, and an Open

Deposon: An Auditable, Conservation-Guaranteed, Game-Theoretically Tested Scattering Layer over LLM Reasoning Paths

model-releasesarxiv-cs-lg

arXiv:2609.09001v1 Announce Type: cross Abstract: Multi-step LLM reasoning lacks a machine-recheckable ledger: discarded reasoning paths leave no auditable record. We propose the Deposon scattering la

Depth-to-Image Synthesis-Driven Generative Unguided Depth Completion

arXiv:2609.06007v1 Announce Type: new Abstract: Guided depth completion methods heavily depend on RGB quality and alignment, while unguided ones often suffer from limited precision due to the absence

Detect Anything in Graphic Design: Element-Level Rewards for Autoregressive Detection

arXiv:2609.07072v1 Announce Type: new Abstract: Graphic designs, such as posters, advertisements, and infographics, are an important medium for communicating information and shaping understanding. Unl

Detecting and explaining clinical-omics inconsistencies to improve patient cohort stratification: an application to Parkinson's disease

arXiv:2507.03656v2 Announce Type: replace Abstract: Discrepancies between clinical diagnoses and omics profiles within a characterized cohort may reflect misdiagnosis, hidden subgroups or prodromal di

Dex-X: Learning Visual-Tactile Dexterous Manipulation From Human Videos with Simulated Interaction

arXiv:2609.07747v1 Announce Type: new Abstract: Human videos are an abundant source of dexterous manipulation behaviors, but they lack tactile information that is crucial for contact-rich interaction.

safetyarxiv-cs-ro

DF26: We Cannot Tell Fake From Real Anymore

model-releasesarxiv-cs-cv

arXiv:2609.07369v1 Announce Type: new Abstract: We introduce DF26, a novel benchmark for detecting AI-generated videos containing fully synthetic clips produced by recent text-to-video and image-to-vi

Diagnosing and Dynamically Filtering Occupancy World Models for Active Mapping

arXiv:2609.06820v1 Announce Type: cross Abstract: Active mapping requires a robot to select camera viewpoints that efficiently reconstruct an unknown 3D scene. To reason about unobserved regions, rece

Diagnosing LLM Reranker Behavior Under Fixed Evidence Pools

arXiv:2602.18613v2 Announce Type: replace Abstract: Standard reranking evaluations study how a reranker orders candidates returned by an upstream retriever. This setup couples ranking behavior with re

Diagonal Attenuation: A Finite-Sample Correction for PCA

arXiv:2609.05796v1 Announce Type: cross Abstract: Principal component analysis (PCA) can rotate away from its population target when a covariance matrix is estimated from limited data. We introduce di

Industry

Did OpenAI just solve Navier–Stokes—and what would that actually mean for AGI? @EMostaque joins me LIVE now to examine the claimed breakthro…

Did OpenAI just solve Navier–Stokes—and what would that actually mean for AGI? @EMostaque joins me LIVE now to examine the claimed breakthrough, what would count as a verified solution, and whether AI

industryemad-mostaque--x

Applications

Differentiable Causal Discovery for Singular Linear Models under Confounding

arXiv:2601.01368v2 Announce Type: replace Abstract: Score-based causal discovery in the presence of unobserved confounders requires both a consistent scoring criterion and an efficient search over gra

applicationsarxiv-cs-lg

Differentially Private Model-X Knockoffs via Johnson-Lindenstrauss Transform

arXiv:2508.04800v2 Announce Type: replace-cross Abstract: We introduce a novel privatization framework for high-dimensional controlled variable selection. Our framework enables rigorous False Discover

Difficulty-Adaptive Tree-Structured Policy Optimization for Expanding Reasoning Coverage in RLVR

arXiv:2609.08650v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has been central to the recent success of Large Reasoning Models. However, while RLVR significantl

Diffuse2Seg: Diffusion Models Can Segment Anything Without Supervision

arXiv:2609.06491v1 Announce Type: new Abstract: Open-world entity segmentation aims to predict masks for arbitrary objects across domains and at multiple granularities, from parts to whole objects. In

Diffusion Model in Latent Space for Medical Image Segmentation Task

arXiv:2512.01292v4 Announce Type: replace Abstract: Medical image segmentation is crucial for clinical diagnosis and treatment planning. Traditional methods typically produce a single segmentation mas

Diffusion models for eye-gaze trajectory generation using position and velocity representations

arXiv:2609.05522v1 Announce Type: new Abstract: Eye-tracking data are expensive to collect, requiring specialized hardware and controlled laboratory conditions, and difficult to share because of priva

Directed mixed membership stochastic blockmodel

arXiv:2101.02307v4 Announce Type: replace-cross Abstract: Mixed membership modeling for undirected networks has been extensively explored in network science over the past few years. Despite the substa

Discovering Natural Transformation Vulnerabilities in Black-Box Vision Models

arXiv:2609.07110v1 Announce Type: new Abstract: Natural adversarial examples (NAEs) reveal that vision models can fail under realistic semantic changes beyond norm-bounded perturbations. However, gene

Discovering Translation-Worthy Languages with E-Values

arXiv:2609.06593v1 Announce Type: cross Abstract: Choosing when to translate multilingual documents is a central routing problem in text classification: translation can improve predictions for some la

Discussing this case tonight at 7:45 eastern time on CBC.

Gary Marcus will discuss his “case for boycotting generative AI” during a CBC segment scheduled to air at 7:45 p.m. ET tonight. The argument is outlined in his Substack post titled *The Case for Boyco

safetygary-marcus--x

DISEIL: Demonstration Distillation for Sample-Efficient Imitation Learning

arXiv:2609.08123v1 Announce Type: cross Abstract: A robot that can be taught a new task from a handful of demonstrations has to work out for itself what it still cannot do, and then ask for exactly th

Disentangling Steering Vectors

arXiv:2609.07037v1 Announce Type: new Abstract: Activation steering has emerged as a lightweight, inference-time approach to control the behavior of Large Language Models (LLMs). However, traditional

Disparity Has a Sign: Stereo Matching Beyond the Zero-Disparity Plane

model-releasesarxiv-cs-cv

arXiv:2609.06809v1 Announce Type: new Abstract: Modern stereo matching models fail when disparity crosses zero, with end-point error (EPE) rising by 4.6-37imes. Yet stereoscopic content, from cinema 3

Distillation as Probability Transport: Routed On-Policy Distillation

arXiv:2609.08337v1 Announce Type: new Abstract: On-policy distillation (OPD) transfers teacher knowledge on student-generated trajectories, but efficient sampled objectives reduce the teacher distribu

Agents

Distributed Dexterous Manipulation with Spatially Conditioned Multi-Agent Transformers

arXiv:2609.06930v1 Announce Type: cross Abstract: Distributed Dexterous Manipulation (DDM) is a novel paradigm that presents significant control challenges due to high action-space redundancy, inter-r

agentsarxiv-cs-lg

Distributed Lag Neural Additive Models

arXiv:2609.07381v1 Announce Type: cross Abstract: We introduce Distributed Lag Neural Additive Models (DLNAMs), neural-additive analogues of Distributed Lag Non-linear Models (DLNMs) for learning nonl

Distributed Secure Learning Control for Large-scale Multirobots under Stealthy Actuator Attacks

arXiv:2609.06896v1 Announce Type: new Abstract: Distributed learning control for multirobot systems (MRS) offers significant flexibility in presence of uncertainties but lacks provable performance gua

safetyarxiv-cs-ro

Distribution-free inference on the number of changepoints

arXiv:2609.08234v1 Announce Type: cross Abstract: Suppose we are given an ordered sequence of independent data whose distribution changes K times at unknown locations, for some unknown K geq 0. In thi

DIVA: Exploiting Cross-Step Conditional Propagation for Visual Jailbreaks in Discrete Diffusion Vision-Language Models

arXiv:2609.05525v1 Announce Type: new Abstract: Large vision-language models (VLMs) are increasingly deployed in safety-critical settings, yet existing visual jailbreak research has focused almost exc

DL^3M: A Vision-to-Language Framework for Expert-Level Medical Reasoning through Deep Learning and Large Language Models

arXiv:2512.13742v3 Announce Type: replace Abstract: Medical image classifiers detect gastrointestinal diseases well, but they do not explain their decisions. Large language models can generate clinica

Do Depressive Facial Patterns Transfer Across Cultures and Contexts? Evidence from a German RCT and E-DAIC

arXiv:2609.05543v1 Announce Type: new Abstract: Automated assessment of depression from facial dynamics holds promise for scalable mental health monitoring, yet cross-corpus generalization of learned

Local Ai

Do Input-Level Defenses Transfer to Observation-Level Attacks on VideoLLMs?

arXiv:2609.08331v1 Announce Type: new Abstract: Video Large Language Models (VideoLLMs) are increasingly deployed in safety-critical applications such as content moderation and video analytics. To pro

local-aiarxiv-cs-cv

Do Quantum AIs Dream in Paths? Path-Integral Slow Thinking through Grover Interference

model-releasesarxiv-cs-lg

arXiv:2609.05842v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards enables large language models to think slowly, but the same training can induce policy collapse: probab

Do Reasoning Representations Help Humans Evaluate LLM Outputs?

arXiv:2609.09038v1 Announce Type: new Abstract: Reasoning representations are increasingly used as explanations for large language model outputs. Yet they are typically evaluated with model-centric cr

Do Reviewers Still Reward Lexical Complexity? A Frozen-Rater Study of Preference Drift in 124K ICLR Reviews

arXiv:2609.08475v1 Announce Type: cross Abstract: Large language models have collapsed the cost of producing lexically elaborate prose, and whether peer reviewers still reward it is a question about t