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Deep Learning-Based Tri-Hybrid Multi-User MIMO Precoding: The Blessing of EM-Reconfigurable Antennas

arXiv:2609.39167v1 Announce Type: cross Abstract: Electromagnetic (EM)-reconfigurable antennas provide multiple candidate radiation patterns per element, thereby introducing an additional EM-domain de

tutorialsarxiv-cs-lg

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Research

Deep Learning for Longitudinal Medical Imaging: A Scoping Review

DGX agent

arXiv:2610.08838v1 Announce Type: cross Abstract: Longitudinal medical imaging analysis is a cornerstone of modern medical practice and patient care. Deep learning applied to longitudinal imaging offe

researcharxiv-cs-cv

8 Oct 2026

DeepTopoClustering: Unsupervised Derivation of Surface Process Taxonomy from 4D Point Clouds for Topographic Monitoring

arXiv:2610.09860v1 Announce Type: new Abstract: 4D point clouds acquired by permanent laser scanning (PLS) enable accurate high-frequency monitoring of surface change in dynamic topographic environmen

DeltaRepresentation: Geometry Supervised Representation Learning of Phenotypes via Counterfactual Reasoning for Medical VLMs

arXiv:2610.10286v1 Announce Type: new Abstract: Medical vision-language models (VLMs) have shown increasing potential for radiological image interpretation. Medical VLMs encode radiological images int

DeltaSplat: Iterative Gaussian Refinement for Pose-Free Feed-Forward 3D Gaussian Splatting

arXiv:2610.09853v1 Announce Type: new Abstract: Pose-free feed-forward 3D Gaussian Splatting (3DGS) reconstructs a scene from sparse, unposed images in a single network pass, removing the need for cam

Local Ai

{Delta}WAM: Distilling Action Tangent Fields into World Action Models

arXiv:2610.09734v1 Announce Type: new Abstract: World Action Models (WAM) improve robot policies by augmenting sparse action supervision with dense future prediction. However, much of the predictable

local-aiarxiv-cs-ro

Hardware

Democratizing MoE inference on commodity GPUs with CoMoE

arXiv:2610.09424v1 Announce Type: cross Abstract: Deploying Mixture-of-Experts (MoE) models relies heavily on Expert Parallelism, which generates intense inter-GPU communication. Consequently, state-o

hardwarearxiv-cs-lg

DenoFlow: Flow Matching for SSVEP Denoising under Real Physiological Artifacts

arXiv:2610.08817v1 Announce Type: new Abstract: Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly steady-state visual evoked potential (SSVEP) systems, are highly vulne

Hardware

Denoising Blocks, Not Tokens: Efficient Compressed Continuous Diffusion with Branching Token Realization

arXiv:2610.09311v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text through iterative parallel refinement, offering the potential for higher throughput than autoregressive (

hardwarearxiv-cs-lg

Depth-to-RGB: Repurposing a Frozen Depth Estimator for Geometry-Guided Compositing

arXiv:2610.09125v1 Announce Type: new Abstract: Reference-based object compositing inserts or replaces an object using a background image, a reference image, and a 2D compositing mask. These inputs gu

tutorialsarxiv-cs-cv

Derivative Gaussian Processes on a Two-Direction Budget

arXiv:2610.10428v1 Announce Type: cross Abstract: Gradient observations promise more accurate Gaussian process (GP) surrogates, but the cost of incorporating them has long stood in the way of realizin

Agents

Design of a Fully Actuated 4-DOF Robotic Finger With Joint-Specific Hybrid Remote Actuation

arXiv:2610.10180v1 Announce Type: new Abstract: This paper presents a fully actuated 4-DOF robotic finger using a joint-specific hybrid remote-actuation architecture. The metacarpophalangeal (MCP) joi

agentsarxiv-cs-ro

Design optimization of tendon-driven robots considering tendon wrapping and shortcut

arXiv:2610.09645v1 Announce Type: new Abstract: This study proposes a multi-objective optimization method for tendon-driven arm design, addressing the inherent trade-off between joint torque and arm t

researcharxiv-cs-ro

Despite Instructions: Frontier Agents Improvise Covert Channels at Test Time

model-releasesarxiv-cs-cl

arXiv:2609.32701v2 Announce Type: replace-cross Abstract: In security-sensitive applications, language-model agents are often required to coordinate without disclosing confidential information. Yet re

Detecting Adversarial Images through Response Profiles of Vision-Language Models

arXiv:2610.10436v1 Announce Type: new Abstract: Adversarial perturbations can alter the predictions of frozen vision-language models (VLMs) while leaving their confidence and image--text similarity pa

Detecting Control and Response Events for AI-Enabled Radio Access Networks

arXiv:2606.06459v2 Announce Type: replace Abstract: Next-generation wireless networks are moving toward the use of concurrent AI-driven control functions to optimize different objectives, particularly

Dialect-Robust Speech Language Models with Synthetic Pseudo-Dialect Augmentation

arXiv:2610.09321v1 Announce Type: new Abstract: Speech Language Model (SLM) performance often degrades on dialects due to data scarcity. Conventional text-to-speech (TTS) augmentation struggles to cov

researcharxiv-cs-cl

Differential Refresh Policies for Models Trained on Lagging Data Snapshots: From a Single-Age Equivalence Limit to an Optimal Per-Segment Allocation

arXiv:2610.09519v1 Announce Type: new Abstract: Production machine-learning models are derived artifacts of time-bounded training snapshots: a deployed model is a materialized view over a training cut

Diffusion-Generated Image Watermarking: A Two-Axis Taxonomy and Three Protocol-Bounded Case Studies

arXiv:2610.09755v1 Announce Type: new Abstract: Watermarking diffusion-generated images requires balancing provenance signals with image quality, robustness, and computational cost. This work organize

Local Ai

Directed Temporal Representations for Offline Visual Control

arXiv:2610.08960v1 Announce Type: new Abstract: Predictive world models provide compact visual representations for control. Control requires a latent geometry aligned with temporal reachability rather

local-aiarxiv-cs-lg

Directional Evidence Guided Search-Space Reduction for Exact DAG Learning

arXiv:2610.09136v1 Announce Type: new Abstract: Learning a directed acyclic graph (DAG) from observational data is a challenging combinatorial problem due to the exponential growth in the number of ca

DisParQ: Self-Supervised Part Concepts for Interpretable Vision Foundation Models

arXiv:2610.09802v1 Announce Type: new Abstract: Concept-based vision models represent images through an intermediate layer of human-inspectable concepts, so what a model relies on can be traced to tho

tutorialsarxiv-cs-cv

DISRQAD: Diffusion Image Super-Resolution Quality Assessment Dataset and Benchmark

arXiv:2610.09077v1 Announce Type: new Abstract: Diffusion-based image super-resolution (SR) can create visually plausible detail that is not supported by the low-resolution input. We introduce DISRQAD

Distilling Graph Geometry: Knowledge Gap from GNNs to MLPs

arXiv:2610.10520v1 Announce Type: new Abstract: GNN-to-MLP distillation aims to retain the predictive accuracy of a message-passing teacher while deploying a graph-free MLP at inference. Existing meth

Applications

Distributed Motion Planning for Multi-Robot Systems under Topological Constraints

arXiv:2610.10065v1 Announce Type: new Abstract: Efficient and distributed coordination of mobile robots is one of the main challenges in multi-robot systems. Topological constraints, often expressed a

applicationsarxiv-cs-ro

DiTS: Multimodal Diffusion Transformers Are Time Series Forecasters

arXiv:2602.06597v2 Announce Type: replace Abstract: While generative modeling facilitates probabilistic time series forecasting, incorporating heterogeneous exogenous information remains challenging.

Do Better Visual Representations Always Lead to Better End-to-End Autonomous Driving?

arXiv:2610.09695v1 Announce Type: cross Abstract: Visual foundation models (VFMs) are increasingly integrated into end-to-end autonomous driving for their powerful representations, yet it remains uncl

Do Generative Priors Align with Human Naturalness Perception?

arXiv:2610.09928v1 Announce Type: new Abstract: Visual generative models are trained to capture the probability distributions of natural images, yet whether their native priors reflect the regularitie

Do Image Editors Follow Depth-Dependent Blur and Aperture Response? A Rendered-Ground-Truth Pilot Audit

arXiv:2610.09344v1 Announce Type: new Abstract: General image editors are asked to make a photo look as if it were taken at f/1.4, yet it is rarely checked whether the blur they add follows thin-lens

Do Vision-Language-Action Models Understand Instructions? A Mechanistic Interpretability Study on Language Grounding

model-releasesarxiv-cs-ro

arXiv:2610.10178v1 Announce Type: new Abstract: Vision-Language-Action models are designed to generalise across environments and task descriptions, raising the question of whether their action generat

Do Vision Models Learn Physical Constraints or Rendering Shortcuts? A Counterfactual Benchmark for Grounded Physical Consistency

arXiv:2610.09205v1 Announce Type: new Abstract: Modern image editing models can satisfy a text instruction while breaking the physics of the edited scene. A new object may cast no shadow, a mirror may

Industry

Docs: OpenAI told investors its annualized revenue was nearing 50B at the end of September, well below the 70B reported by the media based on investor docs (Financial Times)

Financial Times: Docs: OpenAI told investors its annualized revenue was nearing 50B at the end of September, well below the 70B reported by the media based on investor docs — AI giant recently told in

industrytechmeme

Document-Level Text Simplification in Estonian Using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.10378v1 Announce Type: new Abstract: Document-level text simplification involves transformations that go beyond sentence-internal edits, addressing discourse coherence, anaphora resolution,

Applications

Domain-informed Adaptive Sampling for Generalizable PINNs in Metal Additive Manufacturing via Conditional Flow Matching

arXiv:2610.09126v1 Announce Type: new Abstract: Accurate thermal modeling is essential in metal additive manufacturing (AM) for understanding the process-structure-property chain. Physics-informed neu

applicationsarxiv-cs-lg

DSReg: Provably Recovering Individual World Latents without Reconstruction

arXiv:2610.09457v1 Announce Type: new Abstract: Methods that recover individual latent variables of the world, from nonlinear ICA to dictionary learning and causal representation learning, anchor the

DSTNet: Dynamic Spectral Trajectory Network for Causal Multi-Horizon Financial Forecasting

arXiv:2610.09654v1 Announce Type: new Abstract: Wavelet-based financial forecasters typically use the transform only to denoise, or reduce it to a single spectral snapshot at the forecast origin, and

Dual-QK: Sharp Queries and Flat Keys for Prunable 2-bit KV Caches

arXiv:2610.09827v1 Announce Type: new Abstract: Long inputs and extended generation increase the storage and access costs of the key-value (KV) cache. Low-bit quantization reduces storage and memory t

DynStream: Online Streaming 4D Gaussian Reconstruction of Dynamic Worlds from Unposed Video

arXiv:2610.09720v1 Announce Type: new Abstract: Online reconstruction of dynamic 4D scenes from long, unposed streaming videos requires both continuous processing and photorealistic rendering, which e

EASE: Entropy-Adaptive Distribution Shaping for Evading AI-generated Text Detectors

arXiv:2610.09976v1 Announce Type: new Abstract: AI-generated text (AIGT) detection can be sensitive to the decoding choices of the source large language model (LLM). We observe that perturbing next-to

researcharxiv-cs-cl

EC-EarthFlow: Probabilistic emulation of daily transient global climate model simulations with flow matching

arXiv:2610.09715v1 Announce Type: new Abstract: We introduce EC-EarthFlow, a generative flow matching model that emulates simulations from the physical climate model EC-Earth3. The model is trained on

tutorialsarxiv-cs-lg

ECHO: Embodied Camera Observations of Human Object Carrying

arXiv:2610.10438v1 Announce Type: new Abstract: Embodied and assistive agents must do more than recognize objects: they must reason about where an object belongs given the layout of an environment and

ED3R: Energy-Aware Distributed Disaster Detection via Cooperative Agents in Robotic Systems

arXiv:2606.17739v2 Announce Type: replace-cross Abstract: Robotics are expected to support environmental monitoring and disaster detection, where decisions must be made under uncertainty, resource lim

Edge Accuracy Is Not Enough: Why Dynamics-Learned Structure Fails to Transfer to Inverse Problems

arXiv:2610.10213v1 Announce Type: new Abstract: A natural strategy for inverse problems with scarce labelled data is to transfer relational structure learned from abundant forward-simulation data. We

EDiS: Edge Disjoint Subgraph Sparsification Framework for Graph Neural Networks

arXiv:2610.09059v1 Announce Type: new Abstract: Sparse GNN training reduces computation, but deciding which edges to keep can be costly. Reusing one sparse graph is cheap, but locks training to a fixe

Efficient 3D Gaussian Head Avatars for Edge Devices

arXiv:2610.09821v1 Announce Type: new Abstract: Generative 3D Gaussian head avatars provide high-quality, efficient rendering, but synthesising the Gaussian representation remains computationally expe

Efficient Best-of-N policy evaluation for inference-time alignment

arXiv:2610.09250v1 Announce Type: new Abstract: Best-of-N (BoN) is a common inference-time alignment method that selects the highest-scoring response among N samples from a reference model. Evaluating

Efficient Dense Crowd Trajectory Prediction Via Dynamic Clustering

arXiv:2603.18166v1 Announce Type: cross Abstract: Crowd trajectory prediction plays a crucial role in public safety and management, where it can help prevent disasters such as stampedes. Recent works

Efficient Patch-Based Anomaly Detection Fused with Diffusion Driven Generative Modeling for Semiconductor Wafer Bin Map Open Set Anomaly Detection

arXiv:2610.09993v1 Announce Type: new Abstract: Spatial defect signatures on wafer bin maps (WBMs) trace yield loss to specific process faults, yet supervised classifiers recognize only the defect typ