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Data Scaling Laws in Imitation Learning for Robotic Manipulation

arXiv:2410.18647v4 Announce Type: replace Abstract: Data scaling has revolutionized fields like natural language processing and computer vision, providing models with remarkable generalization capabil

safetyarxiv-cs-ro

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DataStates-LLM: Scalable Checkpointing for Transformer Models Using Composable State Providers

DGX agent

arXiv:2601.16956v1 Announce Type: cross Abstract: The rapid growth of Large Transformer-based models, specifically Large Language Models (LLMs), now scaling to trillions of parameters, has necessitate

hardwarearxiv-cs-ai

29 Jun 2026

DDSA: Dual-Domain Strategic Attack for Spatial-Temporal Efficiency in Adversarial Robustness Testing

arXiv:2601.14302v2 Announce Type: replace-cross Abstract: Image transmission and processing systems in resource-critical applications face significant challenges from adversarial perturbations that co

Decentralized Orchestration Architecture for Fluid Computing: A Secure Distributed AI Use Case

arXiv:2603.12001v2 Announce Type: replace-cross Abstract: Distributed AI and IoT applications increasingly execute across heterogeneous resources spanning end devices, edge/fog infrastructure, and clo

local-aiarxiv-cs-lg

Deep Neural Networks Inspired by Differential Equations

arXiv:2510.09685v2 Announce Type: replace-cross Abstract: Deep learning has become a pivotal technology in fields such as computer vision, scientific computing, and dynamical systems, significantly ad

Deep Residual Networks Learn the Geodesic Curve in the Wasserstein Space

arXiv:2102.09235v3 Announce Type: replace Abstract: Recent studies revealed the mathematical connection between deep neural networks (DNNs) and dynamic systems. However, the specific dynamics that DNN

tutorialsarxiv-cs-lg

Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook

arXiv:2411.19537v2 Announce Type: replace-cross Abstract: We survey deepfake generation and detection techniques, covering all deepfake media types: image, video, audio and multimodal content. We iden

Agents

Delayed Verification Destabilizes Multi-Agent LLM Belief: Instability Thresholds and Optimal Corrector Placement

arXiv:2606.27409v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems often rely on verifier and critic agents to suppress hallucinations, but verification is delayed. Durin

agentsarxiv-cs-cl

DeLux: Cross-Modal Local Artifact Restoration in Video Using Neuromorphic Data

arXiv:2606.27576v1 Announce Type: new Abstract: Conventional RGB cameras suffer from lighting artifacts such as flare, glare, flicker, and overexposure, leading to irrecoverable information loss that

tutorialsarxiv-cs-cv

Democratic ICAI: Debating Our Way to Steering Principles from Preferences

arXiv:2606.28294v1 Announce Type: new Abstract: Preference-based alignment often struggles to capture the reasoning that underlies human judgments. Many evaluations rely on multiple interacting criter

safetyarxiv-cs-lg

Denoising ICF Images with Multiplicative Uniform Noise: A Self-Supervised Study Based on the Log-Domain Noisier2Inverse Framework

arXiv:2606.27635v1 Announce Type: new Abstract: This paper documents the implementation and evaluation of a self-supervised denoising framework on Inertial Confinement Fusion (ICF) images corrupted by

Deployment-Side Adaptiveness in Multi-Horizon Volatility Forecasting

arXiv:2606.27688v1 Announce Type: cross Abstract: In financial forecasting, predictive performance depends not only on which model is trained, but also on how the trained model is deployed. We study t

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Derivation of effective gradient flow equations and dynamical truncation of training data in Deep Learning

arXiv:2501.07400v2 Announce Type: replace-cross Abstract: We derive explicit equations governing the cumulative biases and weights in Deep Learning with ReLU activation function, based on gradient des

Developmental approach reveals the statistical learning of Neural Language Models: Transformers generalize from the most abstract statistical patterns

arXiv:2606.27460v1 Announce Type: new Abstract: In this study, we use a developmental approach to investigate the statistical learning and mental representation of neural language models (NLM). A seri

tutorialsarxiv-cs-cl

DexCompose: Reusing Dexterous Policies for Multi-Task Manipulation with a Single Hand

arXiv:2606.28323v1 Announce Type: cross Abstract: Dexterous manipulation policies can solve individual skills, but composing them to perform multiple tasks with a single hand remains challenging. Addi

safetyarxiv-cs-ai

DFM: Difference Feature Modeling with Text-Guided Gated Contrastive Loss for Remote Sensing Image Change Captioning

arXiv:2606.27410v1 Announce Type: cross Abstract: The primary goal of Remote Sensing Image Change Captioning (RSICC) is to automatically generate descriptions of changes between remote sensing images

tutorialsarxiv-cs-lg

DG^VoiC: Speaker Clustering for Fraud Investigation under Real Call-Centre Conditions

arXiv:2606.28048v1 Announce Type: cross Abstract: Insurance fraud remains costly and operationally difficult, particularly in call-centre workflows where many customer interactions begin at FNOL. Whil

Agents

Dialogue to Detection: A Multimodal Hybrid NLP Pipeline for Insurance Fraud Detection

arXiv:2606.28002v1 Announce Type: cross Abstract: Insurance fraud imposes substantial financial losses and operational inefficiencies, raising premiums and impacting trust among legitimate policyholde

agentsarxiv-cs-ai

Difference of Convex Programming in the Wasserstein Space with Applications to MMD Optimization

arXiv:2606.27767v1 Announce Type: new Abstract: Optimizing functionals over the space of probability measures is now ubiquitous in machine learning. A widely used approach is to perform the optimizati

Differentiable design of the PIAA-ZWFS: a flexible wavefront sensor that approaches the fundamental limit

arXiv:2606.28136v1 Announce Type: cross Abstract: Extreme adaptive optics (AO) is necessary for high contrast astronomy at scales of the habitable zone of nearby systems. We seek to evaluate wavefront

Diffusion Model Attribution via Spectral Coupling of Denoiser Responses

arXiv:2606.28092v1 Announce Type: new Abstract: Attributing a generated image to its source diffusion model is a fundamental challenge in provenance verification and intellectual property protection.

DIM-WAM: World-Action Modeling with Diverse Historical Event Memory

arXiv:2606.27677v1 Announce Type: cross Abstract: World-action models have shown promising robot-manipulation performance by jointly predicting future visual states and actions. However, existing meth

local-aiarxiv-cs-cv

Direct Action-Head Injection of A Grounded 3D Point Unlocks Spatial and Task Generalization

arXiv:2606.27663v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models leverage large-scale vision-language pretraining for flexible robot manipulation, yet at test time they remain britt

local-aiarxiv-cs-ro

Directed Graph Topology Inference via Graph Filter Identification

arXiv:2606.27455v1 Announce Type: cross Abstract: We address the problem of inferring a directed network from nodal measurements generated by linear diffusion dynamics on the sought graph. Observation

Directing the World: Fast Autoregressive Video Generation with Compositional Human-Camera Control

arXiv:2606.27964v1 Announce Type: new Abstract: Building interactive world models requires generating realistic videos while maintaining controllable dynamics over long horizons. Autoregressive video

safetyarxiv-cs-cv

Disentangling Continuous-Time Latent Dynamics: Identifiability of Latent SDEs via Diffusion Shifts

arXiv:2606.28228v1 Announce Type: new Abstract: Causal representation learning for time series has developed strong identifiability results in discrete-time latent causal models, but identifiability i

Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding

arXiv:2606.27596v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) exhibit sophisticated reasoning but remain susceptible to object hallucination. Deviating from the prevailing att

Distributed Air-Gap Flux and Rotor-Current Fusion for Operating-Regime Identification in a 10-MW Kaplan Hydrogenerator

arXiv:2606.27800v1 Announce Type: cross Abstract: Reliable monitoring of hydroelectric generators requires descriptors that capture both electrical loading and electromagnetic field behavior. This wor

tutorialsarxiv-cs-lg

Distribution-based deep multiple instance learning for tumor proportion scoring in NSCLC

arXiv:2606.27579v1 Announce Type: cross Abstract: Accurate assessment of tumor proportion score (TPS) in non-small cell lung cancer (NSCLC) is critical for treatment planning and prognosis. Key challe

DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domain

arXiv:2504.16116v4 Announce Type: replace-cross Abstract: The Web3 ecosystem, underpinned by cryptographic primitives and decentralized consensus, represents a high-stakes environment where software v

DMV-Bench: Diagnosing Long-Horizon Multimodal Agents' Visual Memory with Incidental Cue Injection

arXiv:2606.27499v1 Announce Type: cross Abstract: Research on agent memory has matured rapidly, but almost entirely on the text side: few existing benchmarks ask, in an interactive environment, when a

Do Speech Emphasis Models Generalize across Languages and Emotions?

arXiv:2606.27717v1 Announce Type: cross Abstract: Prosodic emphasis varies across languages, emotions, and speaking styles, yet existing emphasis detection models are largely trained and evaluated on

Drifting in the Future: Stabilizing Path Following Drifting on High-Latency Vehicle Systems

arXiv:2606.27914v1 Announce Type: new Abstract: Autonomously controlling and handling a vehicle at and beyond its stability limit is a mathematically and computationally demanding task. Prior demonstr

safetyarxiv-cs-ro

Drop-Then-Recovery: How Redundant Are Vision-Language-Action Models?

arXiv:2606.27755v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models enable instruction-driven robotic manipulation, but they inherit oversized language backbones from pretrained VLMs

Dual-Learning based Penalized Multi-Align Clustering for Multi-View Incomplete and Disorderly Data

arXiv:2606.27984v1 Announce Type: new Abstract: Multimodal feature fusion can effectively capture complex patterns in real-world data by integrating complementary information from different modalities

safetyarxiv-cs-lg

DysLexLens: A Low-Resource LLM Framework for Analysing Dyslexic Learners Insights from Online Forums

arXiv:2606.27619v1 Announce Type: new Abstract: Dyslexic learners increasingly use artificial intelligence (AI) tools to support reading, writing, organisation, and study-related tasks. However, their

safetyarxiv-cs-ai

EchoSonar-R: A Multi-View Reasoning-Enabled Model for Disease Classification and Report Generation in Echocardiography

arXiv:2606.28164v1 Announce Type: new Abstract: Echocardiography is the most widely used non-invasive cardiac imaging modality, providing essential information for cardiovascular diagnosis. Interpreti

safetyarxiv-cs-cv

Applications

Effects of relational graph modularity and depth on the learning performance of neural networks

arXiv:2507.10005v2 Announce Type: replace Abstract: In recent years, graph-based machine learning techniques, such as reinforcement learning and graph neural networks, have garnered significant attent

applicationsarxiv-cs-lg

Efficient and Stable Multi-Dimensional Kolmogorov-Smirnov Distance

arXiv:2504.11299v2 Announce Type: replace-cross Abstract: We revisit extending the Kolmogorov-Smirnov distance between probability distributions to the multi-dimensional setting, and make new argument

Elastic Time: Dynamic Frame Rate Bottlenecks for Neural Audio Coding

arXiv:2606.27320v1 Announce Type: cross Abstract: Neural audio autoencoders have become a core component of compression, feature extraction, and generation. However, while existing systems support var

EMOSH: Expressive Motion and Shape Disentanglement for Human Animation

arXiv:2606.28026v1 Announce Type: new Abstract: High-fidelity and expressive controllable human animation is essential for content creation and digital avatar applications. However, existing methods f

End-to-End Dynamic Sparsity for Resource-Adaptive LLM Inference

arXiv:2606.27743v1 Announce Type: cross Abstract: Large Language Models (LLMs) inference is typically deployed under a static resource assumption, where models execute a fixed computational graph rega

Applications

Enhanced Neural Video Representation Compression across Extreme Complexity and Quality Scales

arXiv:2606.28163v1 Announce Type: cross Abstract: Implicit neural representations (INRs) have recently emerged as a promising approach to video compression, delivering competitive rate-distortion perf

applicationsarxiv-cs-cv

Hardware

Enhancing Co-packaging Optics Enabled Silicon Photonics Security Assurance Hardware Fingerprinting

arXiv:2606.27612v1 Announce Type: cross Abstract: Silicon photonics enables integration of optical components using standard semiconductor processes, greatly improving data communication bandwidth and

hardwarearxiv-cs-cv

Enhancing Numerical Prediction in LLMs via Smooth MMD Alignment

arXiv:2606.27731v1 Announce Type: cross Abstract: Despite their strong general capabilities, large language models (LLMs) often remain unreliable when outputs must be numerically precise. A key reason

local-aiarxiv-cs-ai

EntMTP: Accelerating LLM Inference with Entropy Guided Multi Token Prediction

arXiv:2606.27550v1 Announce Type: new Abstract: Multi-token prediction has been shown to increase data density during training, improve downstream text-generation quality, and serves as the defacto ap

researcharxiv-cs-cl

Estimation--Prediction Tradeoff in Causal Probabilistic Temporal Graphs

model-releasesarxiv-cs-lg

arXiv:2606.28225v1 Announce Type: new Abstract: Temporal link prediction is usually evaluated by predictive performance on unseen edges, but in probabilistic temporal graphs this criterion can conflat

ET-SAM: Efficient Point Prompt Prediction in SAM for Unified Scene Text Detection and Layout Analysis

arXiv:2603.25168v2 Announce Type: replace Abstract: Previous works based on Segment Anything Model (SAM) have achieved promising performance in unified scene text detection and layout analysis. Howeve