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Data centers’ energy demand threatens Trump’s “Made in America” plan

Data centers now account for about 5% of U.S. electricity demand but could triple by 2035 , creating potential conflicts with domestic manufacturing goals. Rising data center construction is outpacing

applicationsars-technica

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Hardware

Data Driven Optimization of GPU efficiency for Distributed LLM-Adapter Serving

DGX agent

arXiv:2602.24044v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) adapters enable low-cost model specialization, but introduce complex caching and scheduling challenges in distribut

hardwarearxiv-cs-ai

7 Jul 2026

Data-Driven Soft Labeling Scales DNA Read Classification to Whole-Body Cell-Type Deconvolution

arXiv:2607.04987v1 Announce Type: new Abstract: Cell-type deconvolution, the task of estimating the proportions of constituent cell types in a heterogeneous biological sample, is a core problem in com

applicationsarxiv-cs-lg

Industry

Data modeling best practices for Amazon Quick Sight multi-dataset relationships

Today, we are excited to announce Multi-Dataset Relationships in Amazon Quick Sight. This new capability lets you define logical relationships between Quick Sight datasets and perform runtime joins at

industryaws-ml-blog

Industry

Data modeling patterns for Amazon Quick Sight multi-dataset relationships

In this post, we shift from concepts to patterns. For each schema, you’ll find a table structure, use cases, implementation steps, and sample SQL queries. We also cover workarounds for advanced scenar

industryaws-ml-blog

Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks

arXiv:2603.14830v3 Announce Type: replace Abstract: Dataset distillation, a training-aware data compression technique, has recently attracted increasing attention as an effective tool for mitigating c

DC-Motion: Decoupling Structure and Details via Discrete-Continuous Tokens for Human Motion Generation

arXiv:2606.14721v2 Announce Type: replace-cross Abstract: Text-to-motion generation requires modeling both global action structure and fine-grained motion dynamics from natural language. Existing appr

researcharxiv-cs-cv

Local Ai

Decentralised Federated Learning over Temporal Networks: The Role of Heterogeneities

arXiv:2607.03171v1 Announce Type: cross Abstract: Decentralised federated learning, based on peer-to-peer communication, is increasingly proposed for on-device training of machine learning models, pro

local-aiarxiv-cs-ai

Decentralized Aggregation of LLM Predictions via Wagering Mechanisms

arXiv:2607.04389v1 Announce Type: new Abstract: It is increasingly common to aggregate predictions from multiple LLMs, each with domain expertise or access to private tools and data, to improve collec

Decentralized Federated Learning by Partial Message Exchange

arXiv:2603.01730v2 Announce Type: replace Abstract: Decentralized federated learning (DFL) has emerged as a transformative server-free paradigm that enables collaborative learning over large-scale het

Decomposed Prompting Does Not Fix Knowledge Gaps, But Helps Models Say 'I Don't Know'

arXiv:2602.04853v2 Announce Type: replace Abstract: Large language models often struggle to recognize their knowledge limits in closed-book question answering, leading to confident hallucinations. Whi

safetyarxiv-cs-cl

Decomposition for Bayesian Networks: Local and Parallel Inference

model-releasesarxiv-cs-lg

arXiv:2607.04650v1 Announce Type: cross Abstract: Probabilistic inference in high-dimensional Bayesian networks is difficult because exact manipulation of the joint distribution scales exponentially w

Deep Generative Spatiotemporal Engression for Probabilistic Forecasting of Epidemics

arXiv:2603.07108v2 Announce Type: replace-cross Abstract: Accurate and reliable forecasting of epidemic incidences is critical for public health preparedness, yet it remains a challenging task due to

Deep Learning-Based Characterization of Detonation-Cell Size Distributions in Soot-Foil Records

model-releasesarxiv-cs-cv

arXiv:2607.03764v1 Announce Type: cross Abstract: The geometric size and regularity of detonation cells are key physical parameters for characterizing detonation waves. Traditional manual measurement

Deep Learning for Dynamic Programming with Recursive Utility

arXiv:2607.04278v1 Announce Type: cross Abstract: We propose the first deep learning algorithm, the Certainty Equivalent Learning (CEL) algorithm, for solving high-dimensional discrete-time dynamic pr

safetyarxiv-cs-lg

Deep Learning for Semen Analysis in Male Infertility: Computer Vision, Multimodal Fusion, and Clinical Translation

arXiv:2607.05311v1 Announce Type: new Abstract: Male infertility contributes substantially to the global infertility burden, and sperm analysis remains central to diagnosis, treatment planning, and as

applicationsarxiv-cs-cv

Deep Learning Network-Temporal Models For Traffic Prediction

arXiv:2603.11475v2 Announce Type: replace Abstract: Accurate prediction of multivariate time series is essential for emerging network intelligent control, observability, and management functions. Exis

Agents

deepagents is our newest open source project - an open source, model agnostic agent harness this is maybe the most important academy course …

deepagents is our newest open source project - an open source, model agnostic agent harness this is maybe the most important academy course we've launched 🎓 New course launch from LangChain Academy: I

agentsharrison-chase--x

Defending from GeoLocalization through Adversarial Road Trips

arXiv:2607.03277v1 Announce Type: new Abstract: Retrieval-based image geolocalization has emerged as a powerful technique for determining the location of a query image by matching it against a large,

Deform360: A Massive Multi-view Visuotactile Dataset for Deformable World Models

model-releasesarxiv-cs-cv

arXiv:2607.05390v1 Announce Type: cross Abstract: Predicting object dynamics (i.e., world modeling) is a fundamental challenge for robotic manipulation, and modeling deformable objects presents a part

DeGenseGS: Geometrically and Semantically Decoupled Surgical Scene Understanding in 4D Gaussian Splatting

arXiv:2607.04761v1 Announce Type: new Abstract: Real-time, text-promptable 4D reconstruction is indispensable for autonomous surgical interaction. Severe misalignment between semantic meaning and phys

Local Ai

DELTA-TTS: Adapting Autoregressive Model into Diffusion Language Model for Text-to-Speech

arXiv:2607.04140v1 Announce Type: cross Abstract: Autoregressive (AR) text-to-speech (TTS) models generate discrete speech tokens sequentially, which makes inference slow and can degrade robustness by

local-aiarxiv-cs-cl

Local Ai

DELTAVID: Enhancing Fine-Grained Spatiotemporal Perception with Cross-Video Differences

arXiv:2607.02551v1 Announce Type: cross Abstract: Video multimodal large language models have made strong progress on open-ended video understanding, but they still lack precise local spatiotemporal p

local-aiarxiv-cs-ai

Demonstrating Generalization Failures via Mixtures of Conditional Policies

arXiv:2607.03478v1 Announce Type: new Abstract: Post-training of frontier language models is conducted on curated task suites, and inevitably leaves a distribution shift between training and deploymen

Denoised Conformal Alignment for Reliable Selection of Conditional Average Treatment Effect Predictions

arXiv:2607.03161v1 Announce Type: cross Abstract: In selective deployment, practitioners act only on a model-chosen subset of individuals based on predicted conditional average treatment effects, but

safetyarxiv-cs-lg

Derivations of Error-State Kalman Filter Kinematics for Globally Applicable Aided Inertial Navigation Systems

arXiv:2607.03211v1 Announce Type: new Abstract: Global navigation systems require state estimation algorithms that handle Earth's curvature, Earth's rotation, and gravitational variations. These facto

researcharxiv-cs-ro

Deriving Benchmarking Datasets from Long-Form Recordings: Challenges and Opportunities

arXiv:2607.03201v1 Announce Type: cross Abstract: Long-form recordings (LFRs) of child-centered audio are ecologically valid sources for studying early language development, but three problems limit t

applicationsarxiv-cs-lg

Deriving Neural Scaling Laws from the statistics of natural language

model-releasesarxiv-cs-ai

arXiv:2602.07488v3 Announce Type: replace-cross Abstract: Despite the fact that experimental neural scaling laws have substantially guided empirical progress in large-scale machine learning, no existi

Designing Touch for Trauma-Informed Social Robots: A Design Space for Direct and Indirect Actuation

arXiv:2607.04981v1 Announce Type: new Abstract: Touch is a fundamental communication modality in human-robot interaction and may support grounding, emotional regulation, and stress reduction in therap

safetyarxiv-cs-ro

DETECT-3B-Omni is Agnostic of Content and Demographics

arXiv:2607.03418v1 Announce Type: cross Abstract: A trustworthy and GDPR-compliant deepfake audio detector must base its decisions on acoustic artifacts, not on what is being said or who is speaking.

researcharxiv-cs-ai

Tutorials

Detecting Answer-Driven Reasoning in LLM-Based Educational Tutors via Truncated Chain-of-Thought Auditing

arXiv:2607.04572v1 Announce Type: new Abstract: Large language model (LLM) tutors often produce fluent step-by-step explanations, but a correct and pedagogically formatted response does not guarantee

tutorialsarxiv-cs-ai

Detecting Architectural Drift in Safety-Critical Firmware through Runtime Trace Analysis

arXiv:2607.03135v1 Announce Type: cross Abstract: Maintaining consistency between architectural design and runtime-observed behavior is challenging in long-lived safety-critical firmware. This paper p

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)

arXiv:2607.04223v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) reduces but does not eliminate hallucination, and existing detectors return a single answer-level score that does

researcharxiv-cs-ai

Determinants and Limits of LLM Security-Tool Orchestration: A Study with HexStrike-AI

model-releasesarxiv-cs-ai

arXiv:2607.02873v1 Announce Type: cross Abstract: Large language model agents driving security tool suites over the Model Context Protocol are increasingly common. Yet the factors that bound their cap

Deterministic Envelopes for Tamed SGLD: Decoupling Stochastic Gradient Noise and Localizing Taming

arXiv:2606.05242v2 Announce Type: replace-cross Abstract: Stochastic gradient Langevin algorithms often use tamed denominators to stabilize superlinear drifts. This paper shows that when the denominat

safetyarxiv-cs-lg

Developing an LLM-Based Feedback System Grounded in Evidence-Centered Design to Support Physics Problem Solving

arXiv:2512.10785v3 Announce Type: replace-cross Abstract: Generative AI offers new opportunities for individualized and adaptive learning, e.g., through large language model (LLM)-based feedback syste

researcharxiv-cs-ai

Tutorials

DGSeg: Dynamic Gating of Semantic-Spatial Guided Predictions for Reasoning Segmentation

arXiv:2607.04779v1 Announce Type: new Abstract: Reasoning segmentation aims to predict pixel-wise masks for targets given complex language queries. Existing approaches leverage Multimodal Large Langua

tutorialsarxiv-cs-cv

Tutorials

Diagnosing Aerial-View Object Detectors with Foundational Image Generative Models

arXiv:2607.02718v1 Announce Type: cross Abstract: Recent advances in large-scale image generative models enable photorealistic scene synthesis with controllable attributes. Beyond data augmentation, t

tutorialsarxiv-cs-ai

DiCE-CIR: Direct Composition Learning for Efficient Zero-Shot Composed Image Retrieval

arXiv:2607.04665v1 Announce Type: new Abstract: Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image from a multimodal query consisting of a reference image and an edit text des

DICT: Data Injection and Contrastive Trajectory Refinement for Conditional Image Generation with Diffusion Models

arXiv:2607.03899v1 Announce Type: new Abstract: Diffusion models have become a dominant paradigm for conditional image generation, yet existing approaches generally follow two directions: task-specifi

Dictionaries, Not Darwin: Set-Level Selection Beats LLM Evolution in Scientific Equation Discovery

model-releasesarxiv-cs-lg

arXiv:2607.04108v1 Announce Type: new Abstract: Large language models are increasingly used as evolutionary engines for scientific discovery: generate candidates, select winners, feed them back as par

Differential Amplifier-Inspired AmpAttention for Multi-View Robotic Manipulation

arXiv:2607.02845v1 Announce Type: cross Abstract: Multi-view robotic manipulation methods with the attention mechanism have recently achieved significant progress in both training efficiency and task

applicationsarxiv-cs-ai

Differentiate the Evaluator, Not the Program: An Efficient Runtime Representation for Neuro-Symbolic Learning

model-releasesarxiv-cs-ai

arXiv:2607.03574v1 Announce Type: cross Abstract: AI systems increasingly propose executable scientific models whose value depends on both their symbolic structure and their fitted continuous paramete

Diffusion-Guided Uncertainty-Aware Delayed Policy Optimization

arXiv:2607.05064v1 Announce Type: new Abstract: Reinforcement learning in real world environments often suffers from severe performance degradation due to delayed feedback. Existing approaches typical

Diffusion learning reveals viable parameter manifolds and compensation geometry in biological dynamical systems

model-releasesarxiv-cs-lg

arXiv:2607.03671v1 Announce Type: cross Abstract: Models of complex systems often have many parameters, yet are constrained by far fewer experimentally accessible observables: similar activity can eme

Diffusion Models are Open-World Affordance Learners: Leveraging Generative Priors for 3D Affordance Learning

model-releasesarxiv-cs-cv

arXiv:2508.01651v2 Announce Type: replace Abstract: 3D affordance grounding aims to understand how diverse objects can be manipulated, making it a cornerstone of embodied interaction. However, prior w

Dimension Reduction for Curves: Simplified and Generalized

arXiv:2607.03112v1 Announce Type: cross Abstract: We revisit random projections for reducing the dimension of high-dimensional polygonal curves. Drawing from the toolbox of randomized linear algebra,

Agents

DIRA-SS:Dynamic Domain Incremental Regularised Adaptation -- Self-Supervised

arXiv:2311.07461v3 Announce Type: replace Abstract: Autonomous systems (AS) often rely on Deep Neural Network (DNN) classifiers to operate in complex and dynamically changing environments. However, du

agentsarxiv-cs-lg