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Dr. RTL: Autonomous Agentic RTL Optimization through Tool-Grounded Self-Improvement

arXiv:2604.14989v2 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have sparked growing interest in automatic RTL optimization for better performance, power, and area

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DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute

DGX agent

arXiv:2604.23815v1 Announce Type: new Abstract: Scientific Deep Research (DR) agents answer user queries by synthesizing research papers into multi-section reports. User feedback can improve their uti

agentsarxiv-cs-cl

28 Apr 2026

Dream-Cubed: Controllable Generative Modeling in Minecraft by Training on Billions of Cubes

arXiv:2604.22847v1 Announce Type: new Abstract: We introduce Dream-Cubed, a large-scale dataset of Minecraft worlds at voxel resolution, and a family of models using cubes as powerful compositional un

DreamAudio: Customized Text-to-Audio Generation with Diffusion Models

arXiv:2509.06027v3 Announce Type: replace-cross Abstract: With the development of large-scale diffusion-based and language-modeling-based generative models, impressive progress has been achieved in te

DRIFT: Transferring Reasoning Priors for Efficient MLLM Fine-Tuning

arXiv:2510.15050v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have made rapid progress, yet their reasoning ability often lags behind strong text-only LLMs. Bridging thi

DriVerse: Navigation World Model for Driving Simulation via Multimodal Trajectory Prompting and Motion Alignment

model-releasesarxiv-cs-ro

arXiv:2504.18576v2 Announce Type: replace Abstract: This paper presents DriVerse, a generative model for simulating navigation-driven driving scenes from a single image and a future trajectory. Previo

DRP: Distilled Reasoning Pruning with Skill-aware Step Decomposition for Efficient Large Reasoning Models

arXiv:2505.13975v4 Announce Type: replace Abstract: While Large Reasoning Models (LRMs) have demonstrated success in complex reasoning tasks through long chain-of-thought (CoT) reasoning, their infere

researcharxiv-cs-cl

Dual Control of Linear Systems from Bilinear Observations with Belief Space Model Predictive Control

arXiv:2604.24663v1 Announce Type: cross Abstract: We study finite-horizon quadratic control of linear systems with bilinear observations, in which the control input affects not only the state dynamics

Dual-domain Multi-path Self-supervised Diffusion Model for Accelerated MRI Reconstruction

arXiv:2503.18836v2 Announce Type: replace-cross Abstract: Magnetic resonance imaging (MRI) is a vital diagnostic tool, but its inherently long acquisition times reduce clinical efficiency and patient

applicationsarxiv-cs-ai

DualGuard: Dual-stream Large Language Model Watermarking Defense against Paraphrase and Spoofing Attack

arXiv:2512.16182v2 Announce Type: replace-cross Abstract: With the rapid development of cloud-based services, large language models have become increasingly accessible through various web platforms. H

applicationsarxiv-cs-cl

DVPO: Distributional Value Modeling-based Policy Optimization for LLM Post-Training

arXiv:2512.03847v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has shown strong performance in LLM post-training, but real-world deployment often involves noisy or incomplete su

DyABD: The Abdominal Muscle Segmentation in Dynamic MRI Benchmark

arXiv:2604.23187v1 Announce Type: cross Abstract: This work introduces DyABD, a novel and complex benchmark dataset of dynamic abdominal MRIs from patients with abdominal hernias and associated high q

Local Ai

DYMAPIA: A Multi-Domain Framework for Detecting AI-based Video Manipulation

arXiv:2604.24426v1 Announce Type: new Abstract: AI-generated media are advancing rapidly, raising pressing concerns for content authenticity and digital trust. We introduce DYMAPIA, a multi-domain Dee

local-aiarxiv-cs-cv

DynProto: Dynamic Prototype Evolution for Out-of-Distribution Detection

arXiv:2604.23729v1 Announce Type: new Abstract: Recent studies show that using potential out-of-distribution (OOD) labels from large corpora as auxiliary information can improve OOD detection in visio

EAD-Net: Emotion-Aware Talking Head Generation with Spatial Refinement and Temporal Coherence

arXiv:2604.23325v1 Announce Type: cross Abstract: Emotionally talking head video generation aims to generate expressive portrait videos with accurate lip synchronization and emotional facial expressio

EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models

arXiv:2602.17419v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) can enrich industrial anomaly detection with semantic descriptions and anomaly reasoning, but they still la

Early Warning of Intraoperative Adverse Events via Transformer-Driven Multi-Label Learning

arXiv:2603.05212v2 Announce Type: replace-cross Abstract: Early warning of intraoperative adverse events plays a vital role in reducing surgical risk and improving patient safety. While deep learning

Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition

arXiv:2203.04153v2 Announce Type: replace Abstract: Sensor-based human activity recognition (HAR) is a paramount technology in the Internet of Things services. HAR using representation learning, which

ECoLAD: Deployment-Oriented Evaluation for Automotive Time-Series Anomaly Detection

arXiv:2603.10926v1 Announce Type: cross Abstract: Time-series anomaly detectors are commonly compared on workstation-class hardware under unconstrained execution. In-vehicle monitoring, however, requi

Edit Where You Mean: Region-Aware Adapter Injection for Mask-Free Local Image Editing

arXiv:2604.23763v1 Announce Type: new Abstract: Large diffusion transformers (DiTs) follow global editing instructions well but consistently leak local edits into unrelated regions, because joint-atte

Efficient Image Annotation via Semi-Supervised Object Segmentation with Label Propagation

arXiv:2604.22992v1 Announce Type: new Abstract: Reliable object perception is necessary for general-purpose service robots. Open-vocabulary detectors struggle to generalize beyond a few classes and fu

Efficient learning by implicit exploration in bandit problems with side observations

arXiv:2604.24555v1 Announce Type: new Abstract: We consider online learning problems under a partial observability model capturing situations where the information conveyed to the learner is between f

Efficient Rationale-based Retrieval: On-policy Distillation from Generative Rerankers based on JEPA

arXiv:2604.23336v1 Announce Type: cross Abstract: Unlike traditional fact-based retrieval, rationale-based retrieval typically necessitates cross-encoding of query-document pairs using large language

safetyarxiv-cs-cl

Efficient VQ-QAT and Mixed Vector/Linear quantized Neural Networks

arXiv:2604.23172v1 Announce Type: new Abstract: In this work, we developed and tested 3 techniques for vector quantization (VQ) based model weight compression. To mitigate codebook collapse and enable

EgoDyn-Bench: Evaluating Ego-Motion Understanding in Vision-Centric Foundation Models for Autonomous Driving

model-releasesarxiv-cs-cl

arXiv:2604.22851v1 Announce Type: cross Abstract: While Vision-Language Models (VLMs) have advanced highlevel reasoning in autonomous driving, their ability to ground this reasoning in the underlying

EgoLive: A Large-Scale Egocentric Dataset from Real-World Human Tasks

arXiv:2604.23570v1 Announce Type: new Abstract: The advancement of robot learning is currently hindered by the scarcity of large-scale, high-quality datasets. While established data collection methods

applicationsarxiv-cs-ro

EL3DD: Extended Latent 3D Diffusion for Language Conditioned Multitask Manipulation

arXiv:2511.13312v2 Announce Type: replace-cross Abstract: Acting in human environments is a crucial capability for general-purpose robots, necessitating a robust understanding of natural language and

ELSA: Exact Linear-Scan Attention for Fast and Memory-Light Vision Transformers

arXiv:2604.23798v1 Announce Type: cross Abstract: Existing attention accelerators often trade exact softmax semantics, depend on fused Tensor Core kernels, or incur sequential depth that limits FP32 t

EMCompress: Video-LLMs with Endomorphic Multimodal Compression

arXiv:2508.21094v3 Announce Type: replace Abstract: Video-LLMs face a fundamental tension in long-video reasoning: static, sparse frame sampling either dilutes evidence across task-irrelevant segments

EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models

arXiv:2502.04424v4 Announce Type: replace-cross Abstract: With the integration of multimodal large language models (MLLMs) into robotic systems and AI applications, embedding emotional intelligence (E

Emotion-Conditioned Short-Horizon Human Pose Forecasting with a Lightweight Predictive World Model

arXiv:2604.23532v1 Announce Type: cross Abstract: Short-term human pose prediction plays a crucial role in interactive systems, assistive robots, and emotion-aware human-computer interaction[1-3]. Whi

EmoTrans: A Benchmark for Understanding, Reasoning, and Predicting Emotion Transitions in Multimodal LLMs

arXiv:2604.23348v1 Announce Type: cross Abstract: Recent multimodal large language models (MLLMs) have shown strong capabilities in perception, reasoning, and generation, and are increasingly used in

Empirical Ablation and Ensemble Optimization of a Convolutional Neural Network for CIFAR-10 Classification

arXiv:2604.23861v1 Announce Type: cross Abstract: Convolutional neural networks (CNNs) remain a central approach in image classification, but their performance depends strongly on architectural and tr

Enabling Transparent Cyber Threat Intelligence Combining Large Language Models and Domain Ontologies

arXiv:2509.00081v2 Announce Type: replace-cross Abstract: Effective Cyber Threat Intelligence (CTI) relies upon accurately structured and semantically enriched information extracted from cybersecurity

End-to-End Learning for Partially-Observed Time Series with PyPOTS

arXiv:2604.24041v1 Announce Type: cross Abstract: Partially-observed time series (POTS) is ubiquitous in real-world applications, yet most existing toolchains separate missing-value handling from down

Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting

model-releasesarxiv-cs-lg

arXiv:2604.24705v1 Announce Type: cross Abstract: Energy forecasting research faces a persistent comparability gap that makes it difficult to measure consistent progress over time. Reported accuracy g

Energy-Aware Routing to Large Reasoning Models

arXiv:2601.00823v2 Announce Type: replace Abstract: Large reasoning models (LRMs) have heterogeneous inference energy costs based on which model is used and how much it reasons. To reduce energy, it i

Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy

arXiv:2604.23426v1 Announce Type: new Abstract: Federated learning (FL) is a distributed machine learning method where multiple devices collaboratively train a model under the management of a central

Enhancing molecular dynamics with equivariant machine-learned densities

arXiv:2604.24563v1 Announce Type: cross Abstract: Machine-learning interatomic potentials (MLIPs) have enabled molecular dynamics at near ab initio accuracy, yet remain limited to energies and forces

Epicure: Multidimensional Flavor Structure in Food Ingredient Embeddings

arXiv:2604.22776v1 Announce Type: cross Abstract: A chef's intuition about flavor, texture, and cultural identity represents tacit knowledge that is difficult to articulate yet central to culinary pra

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce

arXiv:2604.23993v1 Announce Type: cross Abstract: Product mapping, the task of deciding whether two e-commerce listings refer to the same product, is a core problem for price monitoring and channel vi

Equivariant Filter for Radar-Inertial Odometry

arXiv:2604.23033v1 Announce Type: new Abstract: Radar-Inertial Odometry (RIO) based on the Extended Kalman Filter (EKF) relies on accurate extrinsic calibration between the radar and the Inertial Meas

applicationsarxiv-cs-ro

Escher-Loop: Mutual Evolution by Closed-Loop Self-Referential Optimization

arXiv:2604.23472v1 Announce Type: new Abstract: While recent autonomous agents demonstrate impressive capabilities, they predominantly rely on manually scripted workflows and handcrafted heuristics, i

ESIA: An Energy-Based Spatiotemporal Interaction-Aware Framework for Pedestrian Intention Prediction

arXiv:2604.23728v1 Announce Type: cross Abstract: Recent advances in autonomous driving have motivated research on pedestrian intention prediction, which aims to infer future crossing decisions and ac

ESPADA: Execution Speedup via Semantics Aware Demonstration Data Downsampling for Imitation Learning

arXiv:2512.07371v3 Announce Type: replace-cross Abstract: Behavior-cloning based visuomotor policies enable precise manipulation but often inherit the slow, cautious tempo of human demonstrations, lim

applicationsarxiv-cs-ai

Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach

model-releasesarxiv-cs-lg

arXiv:2601.18399v2 Announce Type: replace Abstract: Separating liquid-liquid dispersions in gravity settlers is critical in chemical, pharmaceutical, and recycling processes. The dense-packed zone hei

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

arXiv:2604.23466v1 Announce Type: cross Abstract: NVIDIA's CUDA Tile (CuTile) introduces a Python-based, tile-centric abstraction for GPU kernel development that aims to simplify programming while ret

Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards

arXiv:2604.23341v1 Announce Type: cross Abstract: The deployment of Large Language Models (LLMs) as assistants in electric grid operations promises to streamline compliance and decision-making but exp