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Device Context Protocol: A Compact, Safety-First Architecture for LLM-Driven Control of Constrained Devices

arXiv:2605.26159v1 Announce Type: cross Abstract: Large language models are increasingly used as orchestrators of external tools via the Model Context Protocol (MCP), but MCP is built for software ser

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Model Releases

DGLD: Domain-Gated Latent Diffusion for the Discovery of Novel Energetic Materials

DGX agent

arXiv:2605.26540v1 Announce Type: cross Abstract: Energetic-materials performance gains translate directly into reduced propellant mass, smaller warheads, and more efficient civilian gas-generators, y

model-releasesarxiv-cs-ai

27 May 2026

DIANOIA: Diagnostic Decomposition and Joint Optimization for Multi-Agent Reasoning

arXiv:2602.08586v3 Announce Type: replace Abstract: Multi-agent LLM systems consistently outperform single-agent baselines, yet practitioners still cannot predict which design works for a new task or

Diffuse to Detect: Generative Diffusion Models for Unsupervised IC Anomaly Detection

arXiv:2605.26468v1 Announce Type: cross Abstract: Latent defect screening is challenged by extremely low failure rates, high-dimensional test data, and absence of labeled anomalies. We propose the fir

Dimensional Distribution Emotion State: Leveraging Valence and Arousal as a Common Embedding Space for Visual Emotion Analysis

arXiv:2605.26262v1 Announce Type: new Abstract: Museums are important sites for the dissemination of culture and art. They are institutions rooted in history and tradition; their exhibitions are often

safetyarxiv-cs-cv

Applications

DinoComplete: 3D Shape Completion with Distilled Semantic Priors and State Space Models

arXiv:2605.26949v1 Announce Type: new Abstract: 3D shape completion from partial scans remains challenging for unseen categories and noisy real-world observations, where geometry alone is often insuff

applicationsarxiv-cs-cv

DirectFisheye-GS: Enabling Native Fisheye Input in Gaussian Splatting with Cross-View Joint Optimization

arXiv:2604.00648v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has enabled efficient 3D scene reconstruction from everyday images with real-time, high-fidelity rendering, greatly adv

researcharxiv-cs-cv

Agents

Disentangled Representation Learning through Unsupervised Symmetry Group Discovery

arXiv:2603.11790v3 Announce Type: replace Abstract: Symmetry-based disentangled representation learning leverages the group structure of environment transformations to uncover the latent factors of va

agentsarxiv-cs-lg

Tutorials

Dissecting Multimodal In-Context Learning: Modality Asymmetries and Circuit Dynamics in modern Transformers

arXiv:2601.20796v2 Announce Type: replace Abstract: Transformer-based multimodal large language models often exhibit in-context learning (ICL) abilities. Motivated by this phenomenon, we ask: how do t

tutorialsarxiv-cs-cl

Local Ai

Distributed Control of Network Systems in the Space of Stabilizing Graph Neural Network Policies

arXiv:2512.18540v2 Announce Type: replace-cross Abstract: We study distributed control of networked systems through reinforcement learning, where neural policies must be simultaneously scalable, expre

local-aiarxiv-cs-lg

Distribution-Aware Conformal Prediction: A Framework for generating efficient prediction intervals for time series

arXiv:2605.26569v1 Announce Type: new Abstract: We present Distribution-aware Conformal Prediction (DCP), a unified framework integrating probabilistic predictors like Monte Carlo dropout, deep ensemb

Applications

Do Modern Post-Hoc Watermarking Methods Beat Broken-Arrows?

arXiv:2605.27135v1 Announce Type: cross Abstract: With the rapid proliferation of generative models, such as diffusion models, digital watermarking has emerged as a crucial solution for identifying AI

applicationsarxiv-cs-cv

Doc-CoB: Enhancing Document Understanding with Visual Chain-of-Boxes Reasoning

arXiv:2505.18603v2 Announce Type: replace Abstract: Document understanding aims to perform question answering and information extraction over document images, where the visual content is highly inform

Drive-P2D: A Progressive Perception-to-Decision Benchmark for VLMs in Autonomous Driving

arXiv:2601.14702v2 Announce Type: replace Abstract: Autonomous driving requires reliable perception and safe decision-making in complex scenarios. Recent vision-language models (VLMs) demonstrate reas

DSA-Tokenizer: Disentangled Semantic-Acoustic Tokenization via Flow Matching-based Hierarchical Fusion

arXiv:2601.09239v3 Announce Type: replace-cross Abstract: Speech tokenizers are a key building block of fully discrete Speech LLMs. Existing tokenizers either prioritize semantic encoding, fuse semant

Dual-Thresholded Heatmap-Guided Proposal Clustering and Negative Certainty Supervision with Enhanced Base Network for Weakly Supervised Object Detection

arXiv:2509.08289v3 Announce Type: replace Abstract: Weakly supervised object detection (WSOD) has attracted significant attention in recent years, as it does not require box-level annotations. State-o

researcharxiv-cs-cv

DunbaaBERT: From Sacrifice to Semantics

arXiv:2605.26935v1 Announce Type: new Abstract: Large language models have achieved strong performance across many NLP tasks, yet Urdu remains comparatively underexplored due to limited resources and

DuoGesture: Neuro-Inspired and Biomechanically Informed Dual-Stream Co-Speech Gesture Generation

arXiv:2605.26236v1 Announce Type: new Abstract: Co-speech gesture generation requires both semantic expressivity and biomechanically plausible rhythmic motion. Existing holistic gesture models mix lex

safetyarxiv-cs-cv

DV-SFT: Direct Vision Supervision for Fine-Grained Visual Understanding

arXiv:2605.26656v1 Announce Type: new Abstract: Multimodal large language models are typically trained end-to-end to predict ground-truth answers, yet supervision signals are applied exclusively to te

safetyarxiv-cs-cv

Applications

Dynamic Link Prediction with Temporally Enhanced Signed Graph Neural Networks

arXiv:2605.26290v1 Announce Type: new Abstract: Temporal signed networks (TSNs) model the time evolution of cooperative and adversarial relationships that arise in applications such as social media an

applicationsarxiv-cs-lg

Tutorials

DynFrame: Adaptive Reasoning-Driven Multimodal Framework with Dynamic Frame Augmentation for Complex Video Understanding

arXiv:2605.26680v1 Announce Type: cross Abstract: Recent video multimodal large language models (MLLMs) increasingly couple step-by-step reasoning with on-demand visual evidence retrieval, allowing mo

tutorialsarxiv-cs-ai

E3: Issue-Level Backtesting for Automated Research Critique

arXiv:2605.27072v1 Announce Type: cross Abstract: We present E3, an automated review assistant that augments reviewers and engineering teams by identifying decision-relevant technical concerns in rese

E^3C: Video Generation with 3D Environmental Memory and Ego-Exo Human Pose Control

arXiv:2605.26316v1 Announce Type: cross Abstract: Controllable and physically grounded egocentric video generation is essential for embodied agents to reason about how their own and others' actions ma

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning

arXiv:2602.02192v5 Announce Type: replace Abstract: Reinforcement learning (RL) is a critical stage in post-training large language models (LLMs), involving repeated interaction between rollout genera

EconCausal: A Context-Aware Economic Reasoning Benchmark for Large Language Models

arXiv:2510.07231v4 Announce Type: replace-cross Abstract: Socio-economic causal effects depend heavily on their institutional and environmental contexts. The same intervention can produce different, e

ECSEL: Explainable Classification via Signomial Equation Learning

arXiv:2601.21789v2 Announce Type: replace-cross Abstract: We introduce ECSEL, an explainable classification method that learns formal expressions in the form of signomial equations, motivated by the o

Local Ai

Edge AI Deployment Beyond Models: A BSP-Aware Systems Framework for Industrial Embedded Platforms

arXiv:2605.26119v1 Announce Type: cross Abstract: Industrial Edge AI programs often begin with the model and only later confront the platform. That sequencing is attractive because it allows early dem

local-aiarxiv-cs-ai

EdgeFlow: Edge-Map Augmented VLM-Based Flowchart Processing for Industrial Requirements Engineering

arXiv:2605.27332v1 Announce Type: cross Abstract: Flowcharts are widely used in industrial requirements, but usually remain embedded as static images. Vision Language Models (VLMs) show promise in the

EEG-FM-Audit: A Systematic Evaluation and Analysis Pipeline for EEG Foundation Models

arXiv:2605.26910v1 Announce Type: cross Abstract: Large EEG Foundation Models (FMs) have shown great potential for decoding EEG signals across diverse cognitive tasks. However, existing EEG-FM studies

Efficient Agentic Reinforcement Learning with On-Policy Intrinsic Knowledge Boundary Enhancement

arXiv:2605.26952v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) has proven effective for training LLM-based agents with external tool-use capabilities. However, we identify that ag

safetyarxiv-cs-cl

Local Ai

Efficient All-Pairs Correlation Volume Sampling for Optical Flow Estimation

arXiv:2505.16942v2 Announce Type: replace Abstract: Recent optical flow estimation methods often employ local cost sampling from a dense all-pairs correlation volume. This results in quadratic computa

local-aiarxiv-cs-cv

Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNN

arXiv:2210.02573v5 Announce Type: replace Abstract: Learning the physical simulation on large-scale meshes with flat Graph Neural Networks (GNNs) and stacking Message Passings (MPs) is challenging due

researcharxiv-cs-lg

Efficient On-policy Visual-RL via Stochastic Decoupled Policy Gradient

arXiv:2605.26478v1 Announce Type: cross Abstract: We present the stochastic decoupled policy gradient (SDPG), a lightweight visual reinforcement learning (RL) method that trains diverse visuomotor con

Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames

arXiv:2506.09398v3 Announce Type: replace Abstract: We consider the task of predicting Hamiltonian matrices to accelerate electronic structure calculations, which plays an important role in physics, c

EgoProx: Evaluating MLLMs on Egocentric 3D Proximity Reasoning Across a Cognitive Hierarchy

model-releasesarxiv-cs-cv

arXiv:2605.24456v2 Announce Type: replace Abstract: Humans constantly reason about 3D proximity, the relations between their body and surrounding objects, to guide perception and action in daily life.

EHRSummarizer: A Privacy-Aware, FHIR-Native Reference Architecture for Source-Grounded EHR Summarization

arXiv:2601.01668v2 Announce Type: replace-cross Abstract: Clinicians routinely navigate fragmented electronic health record (EHR) interfaces to assemble a coherent picture of a patient's problems, med

Elias in the Lighthouse, Again? Diagnosing Low Diversity in LLM Stories

arXiv:2605.26492v1 Announce Type: cross Abstract: LLM-generated stories are a popular use case, but they show very low variability. We sample 20,000 total stories from four current models using five p

Emergent Causal-Geometric Dynamics Across Depth in Large Language Models

arXiv:2602.04931v2 Announce Type: replace-cross Abstract: Geometric analyses of large language model (LLM) representations reveal structured variation across depth but remain fundamentally correlation

EmoDistill: Offline Emotion Skill Distillation for Language Model Agents in Adversarial Negotiation

arXiv:2605.26785v1 Announce Type: cross Abstract: Post-trained LLMs are often optimized to align responses with human preferences, making them safe, polite, and conversationally appropriate. In advers

Enabling Extensible Embodied Capabilities with Tools

arXiv:2605.26637v1 Announce Type: new Abstract: Most existing embodied intelligence methods formulate perception, reasoning, planning, and control within a unified parameterized policy. Yet these capa

safetyarxiv-cs-ro

Energy-Gated Attention and Wavelet Positional Encoding: Complementary Inductive Biases for Transformer Attention

arXiv:2605.26355v1 Announce Type: cross Abstract: Standard transformer attention computes pairwise token similarity but treats all tokens as equally salient and all positions as equally local, regardl

researcharxiv-cs-cl

Enhancing Autonomous Online Intrusion Detection for IoT with Balanced Learning, Reliable Pseudo-Labels, and Lightweight Architectures

arXiv:2605.26166v1 Announce Type: cross Abstract: The rapid proliferation of Internet of Things (IoT) devices has created an urgent demand for adaptive, resource-efficient Intrusion Detection Systems

ENPMR-Bench: Benchmarking Proactive Memory Retrieval for Emotional Support Agents

arXiv:2605.27240v1 Announce Type: new Abstract: Memory-augmented language agents are increasingly deployed in affective applications such as emotional support, where understanding and responding to us

Entropy Sentinel: Continuous LLM Accuracy Monitoring from Decoding Entropy Traces in STEM

arXiv:2601.09001v4 Announce Type: replace Abstract: Deploying LLMs raises two coupled challenges: (1) monitoring--estimating where a model underperforms as traffic and domains drift--and (2) improveme

EpiCurveBench: Evaluating VLMs on Epidemic Curve Digitization

arXiv:2605.27195v1 Announce Type: new Abstract: Chart-to-data extraction with vision-language models (VLMs) is increasingly evaluated on benchmarks that show diminishing headroom (frontier VLMs exceed

EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering and Reasoning

arXiv:2601.03471v3 Announce Type: replace-cross Abstract: Reliable epidemiological reasoning requires synthesizing study evidence to infer disease burden, transmission dynamics, and intervention effec

Equivariant Filter for Relative Attitude and Target's Angular Velocity Estimation

arXiv:2506.06016v3 Announce Type: replace-cross Abstract: Accurate estimation of the relative attitude and angular velocity between two rigid bodies is fundamental in aerospace applications such as sp

researcharxiv-cs-ro

Erased but Exploitable: Black-box Embedding-Aware Prompting Against Unlearned Text-to-Image Diffusion Models

arXiv:2605.26332v1 Announce Type: cross Abstract: Machine unlearning aims to remove specific concepts from pretrained text-to-image diffusion models, yet several white- and black-box attacks have been