Search: “inference”

Simple Self-Conditioning Adaptation for Masked Diffusion Models

arXiv:2604.26985v1 Announce Type: cross Abstract: Masked diffusion models (MDMs) generate discrete sequences by iterative denoising under an absorbing masking process. In standard masked diffusion, if

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SpaAct: Spatially-Activated Transition Learning with Curriculum Adaptation for Vision-Language Navigation

DGX agent

arXiv:2604.27620v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) aims to enable an embodied agent to follow natural-language instructions and navigate to a target location in unsee

agentsarxiv-cs-cv

1 May 2026

Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework

arXiv:2604.27574v1 Announce Type: cross Abstract: Channel fingerprint (CF) is considered a key enabler for facilitating the acquisition of channel state information (CSI) in massive multiple-input mul

Step-level Optimization for Efficient Computer-use Agents

arXiv:2604.27151v1 Announce Type: new Abstract: Computer-use agents provide a promising path toward general software automation because they can interact directly with arbitrary graphical user interfa

Stop Holding Your Breath: CT-Informed Gaussian Splatting for Dynamic Bronchoscopy

arXiv:2604.28179v1 Announce Type: new Abstract: Bronchoscopic navigation relies on registering endoscopic video to a preoperative CT scan, but respiratory motion deforms the airway by 5-20 mm, creatin

researcharxiv-cs-cv

Targeted Linguistic Analysis of Sign Language Models with Minimal Translation Pairs

model-releasesarxiv-cs-cl

arXiv:2604.27232v1 Announce Type: new Abstract: Models of sign language have historically lagged behind those for spoken language (text and speech). Recent work has greatly improved their performance

TeD-Loc: Text Distillation for Weakly Supervised Object Localization

arXiv:2501.12632v2 Announce Type: replace Abstract: Weakly supervised object localization (WSOL) models are trained using only image-level class labels. They can predict both the object class and spat

local-aiarxiv-cs-cv

Tell-Tale Watermarks for Explanatory Reasoning in Synthetic Media Forensics

arXiv:2509.05753v2 Announce Type: replace-cross Abstract: The rise of synthetic media has blurred the boundary between reality and fabrication under the evolving power of artificial intelligence, fuel

TopBench: A Benchmark for Implicit Prediction and Reasoning over Tabular Question Answering

arXiv:2604.28076v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced Table Question Answering, where most queries can be answered by extracting information or simple aggregatio

Towards All-Day Perception for Off-Road Driving: A Large-Scale Multispectral Dataset and Comprehensive Benchmark

arXiv:2604.27499v1 Announce Type: new Abstract: Off-road nighttime autonomous driving suffers from unreliable visible-light perception, making infrared modality crucial for accurate freespace detectio

Training-Free Reward-Guided Image Editing via Trajectory Optimal Control

arXiv:2509.25845v3 Announce Type: replace-cross Abstract: Recent advancements in diffusion and flow-matching models have demonstrated remarkable capabilities in high-fidelity image synthesis. A promin

Training-Free Tunnel Defect Inspection and Engineering Interpretation via Visual Recalibration and Entity Reconstruction

arXiv:2604.27928v1 Announce Type: cross Abstract: Tunnel inspection requires outputs that can support defect localization, measurement, severity grading, and engineering documentation. Existing traini

local-aiarxiv-cs-ai

Transformer-Empowered Actor-Critic Reinforcement Learning for Sequence-Aware Service Function Chain Partitioning

arXiv:2504.18902v2 Announce Type: replace-cross Abstract: In the forthcoming era of 6G networks, characterized by unprecedented data rates, ultra-low latency, and ubiquitous connectivity, effective ma

A Decision-Theoretic Formalisation of Steganography With Applications to LLM Monitoring

arXiv:2602.23163v3 Announce Type: replace Abstract: Large language models are beginning to show steganographic capabilities. Such capabilities could allow misaligned models to evade oversight mechanis

A Systematic Comparison of Prompting and Multi-Agent Methods for LLM-based Stance Detection

model-releasesarxiv-cs-cl

arXiv:2604.26319v1 Announce Type: new Abstract: Stance detection identifies the attitude of a text author toward a given target. Recent studies have explored various LLM-based strategies for this task

AdaMem: Adaptive User-Centric Memory for Long-Horizon Dialogue Agents

model-releasesarxiv-cs-cl

arXiv:2603.16496v2 Announce Type: replace Abstract: Large language model (LLM) agents increasingly rely on external memory to support long-horizon interaction, personalized assistance, and multi-step

Assessing the Utility of Volumetric Motion Fields for Radar-based Precipitation Nowcasting with Physics-informed Deep Learning

arXiv:2603.13589v2 Announce Type: replace-cross Abstract: Estimating motion from spatiotemporal geoscientific data is a fundamental component of many environmental modeling and forecasting tasks. In t

Beyond Fixed Formulas: Data-Driven Linear Predictor for Efficient Diffusion Models

arXiv:2604.26365v1 Announce Type: new Abstract: To address the high sampling cost of Diffusion Transformers (DiTs), feature caching offers a training-free acceleration method. However, existing method

Breaking the Rigid Prior: Towards Articulated 3D Anomaly Detection

arXiv:2604.26868v1 Announce Type: new Abstract: Existing 3D anomaly detection methods are built on a rigid prior: normal geometry is pose-invariant and can be canonicalized through registration or ali

Applications

CheXthought: A global multimodal dataset of clinical chain-of-thought reasoning and visual attention for chest X-ray interpretation

arXiv:2604.26288v1 Announce Type: cross Abstract: Chest X-ray interpretation is one of the most frequently performed diagnostic tasks in medicine and a primary target for AI development, yet current v

applicationsarxiv-cs-ai

CoFL: Continuous Flow Fields for Language-Conditioned Navigation

arXiv:2603.02854v2 Announce Type: replace-cross Abstract: Existing language-conditioned navigation systems typically rely on modular pipelines or trajectory generators, but the latter use each scene--

local-aiarxiv-cs-ai

CogRAG+: Cognitive-Level Guided Diagnosis and Remediation of Memory and Reasoning Deficiencies in Professional Exam QA

arXiv:2604.25928v1 Announce Type: new Abstract: Professional domain knowledge underpins human civilization, serving as both the basis for industry entry and the core of complex decision-making and pro

researcharxiv-cs-cl

Safety

Data-Centric Foundation Models in Computational Healthcare: A Survey

arXiv:2401.02458v3 Announce Type: replace-cross Abstract: The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a wave of opportunities in computational healthcare. Th

safetyarxiv-cs-ai

Safety

DC-Ada: Reward-Only Decentralized Sensor Adaptation for Heterogeneous Multi-Robot Teams

arXiv:2604.03905v2 Announce Type: replace-cross Abstract: Heterogeneity is a defining feature of deployed multi-robot teams: platforms often differ in sensing modalities, ranges, fields of view, and f

safetyarxiv-cs-ai

Decoupled Prototype Matching with Vision Foundation Models for Few-Shot Industrial Object Detection

arXiv:2604.26404v1 Announce Type: new Abstract: Industrial object detection systems typically rely on large annotated datasets, which are expensive to collect and challenging to maintain in industrial

Domain-Adapted Small Language Models for Reliable Clinical Triage

arXiv:2604.26766v1 Announce Type: cross Abstract: Accurate and consistent Emergency Severity Index (ESI) assignment remains a persistent challenge in emergency departments, where highly variable free-

eDySec: A Deep Learning-based Explainable Dynamic Analysis Framework for Detecting Malicious Packages in PyPI Ecosystem

arXiv:2604.26219v1 Announce Type: cross Abstract: The security of open-source software repositories is increasingly threatened by next-gen software supply chain attacks. These attacks include multipha

researcharxiv-cs-lg

Efficient Zero-Shot Inpainting with Decoupled Diffusion Guidance

arXiv:2512.18365v2 Announce Type: replace Abstract: Diffusion models have emerged as powerful priors for image editing tasks such as inpainting and local modification, where the objective is to genera

local-aiarxiv-cs-cv

Exploring the Potential of Probabilistic Transformer for Time Series Modeling: A Report on the ST-PT Framework

arXiv:2604.26762v1 Announce Type: cross Abstract: The Probabilistic Transformer (PT) establishes that the Transformer's self-attention plus its feed-forward block is mathematically equivalent to Mean-

FlowS: One-Step Motion Prediction via Local Transport Conditioning

model-releasesarxiv-cs-ro

arXiv:2604.26065v1 Announce Type: new Abstract: Generative motion prediction must satisfy three simultaneous requirements for real-world autonomy: high accuracy, diverse multimodal futures, and strict

Applications

GaitKD: A Universal Decoupled Distillation Framework for Efficient Gait Recognition

arXiv:2604.26255v1 Announce Type: new Abstract: Gait recognition is an attractive biometric modality for long-range and contact-free identification, but high-performing gait models often rely on deep

applicationsarxiv-cs-cv

Agents

Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation

arXiv:2604.26787v1 Announce Type: new Abstract: We consider the problems of computing the optimal rank-1 Hankel and Toeplitz-structured approximation of arbitrary matrices under L_2 and L_1-norm error

agentsarxiv-cs-lg

Integrating Weather Foundation Model and Satellite to Enable Fine-Grained Solar Irradiance Forecasting

arXiv:2603.14845v3 Announce Type: replace-cross Abstract: Accurate day-ahead solar irradiance forecasting is essential for integrating solar energy into the power grid. However, it remains challenging

Lyapunov-Guided Self-Alignment: Test-Time Adaptation for Offline Safe Reinforcement Learning

arXiv:2604.26516v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) agents often fail when deployed, as the gap between training datasets and real environments leads to unsafe behavi

MemOVCD: Training-Free Open-Vocabulary Change Detection via Cross-Temporal Memory Reasoning and Global-Local Adaptive Rectification

arXiv:2604.26774v1 Announce Type: cross Abstract: Open-vocabulary change detection aims to identify semantic changes in bi-temporal remote sensing images without predefined categories. Recent methods

Tutorials

MetaSR: Content-Adaptive Metadata Orchestration for Generative Super-Resolution

arXiv:2604.26244v1 Announce Type: cross Abstract: We study generative super-resolution (SR) in real-world scenarios where content and degradations vary across domains, genres, and segments. For exampl

tutorialsarxiv-cs-ai

Tutorials

Mixture of Experts Framework in Machine Learning Interatomic Potentials for Atomistic Simulations

arXiv:2604.26143v1 Announce Type: cross Abstract: First-principles atomistic simulations are essential for understanding complex material phenomena but are fundamentally limited by their computational

tutorialsarxiv-cs-lg

Occam's Razor is Only as Sharp as Your ELBO

arXiv:2604.25984v1 Announce Type: cross Abstract: The marginal likelihood, also known as the evidence, is regarded as a mathematical embodiment of Occam's razor, enabling model selection that avoids o

researcharxiv-cs-lg

Safety

Operating-Layer Controls for Onchain Language-Model Agents Under Real Capital

arXiv:2604.26091v1 Announce Type: new Abstract: We study reliability in autonomous language-model agents that translate user mandates into validated tool actions under real capital. The setting is DX

safetyarxiv-cs-ai

q3-MuPa: Quick, Quiet, Quantitative Multi-Parametric MRI using Physics-Informed Diffusion Models

arXiv:2512.23726v2 Announce Type: replace-cross Abstract: The 3D fast silent multi-parametric mapping sequence with zero echo time (MuPa-ZTE) is a novel quantitative MRI (qMRI) acquisition that enable

Quantamination: Dynamic Quantization Leaks Your Data Across the Batch

arXiv:2604.26505v1 Announce Type: cross Abstract: Dynamic quantization emerged as a practical approach to increase the utilization and efficiency of the machine learning serving flow. Unlike static qu

researcharxiv-cs-lg

ReGATE: Learning Faster and Better with Fewer Tokens in MLLMs

arXiv:2507.21420v3 Announce Type: replace-cross Abstract: The computational cost of training multimodal large language models (MLLMs) grows rapidly with the number of processed tokens. Existing effici

researcharxiv-cs-cl

SAND: Spatially Adaptive Network Depth for Fast Sampling of Neural Implicit Surfaces

arXiv:2604.25936v1 Announce Type: cross Abstract: Implicit neural representations are powerful for geometric modeling, but their practical use is often limited by the high computational cost of networ

local-aiarxiv-cs-cv

SecMate: Multi-Agent Adaptive Cybersecurity Troubleshooting with Tri-Context Personalization

arXiv:2604.26394v1 Announce Type: cross Abstract: Recent advances in large language models and agentic frameworks have enabled virtual customer assistants (VCAs) for complex support. We present SecMat

local-aiarxiv-cs-ai

Select to Think: Unlocking SLM Potential with Local Sufficiency

arXiv:2604.26940v1 Announce Type: new Abstract: Small language models (SLMs) offer computational efficiency for scalable deployment, yet they often fall short of the reasoning power exhibited by their

local-aiarxiv-cs-cl

SG-UniBuc-NLP at SemEval-2026 Task 6: Multi-Head RoBERTa with Chunking for Long-Context Evasion Detection

arXiv:2604.26375v1 Announce Type: cross Abstract: We describe our system for SemEval-2026 Task 6 (CLARITY: Unmasking Political Question Evasions), which classifies English political interview response

SnapPose3D: Diffusion-Based Single-Frame 2D-to-3D Lifting of Human Poses

arXiv:2604.26620v1 Announce Type: new Abstract: Depth ambiguity and joint uncertainty are the two main obstacles in obtaining accurate human pose predictions by 2D-to-3D lifting methods proposed in th

researcharxiv-cs-cv

SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness

arXiv:2604.26341v1 Announce Type: new Abstract: Recent unified image generation models have achieved remarkable success by employing MLLMs for semantic understanding and diffusion backbones for image

researcharxiv-cs-cv