Search: “papers”

arXiv:2603.05842v2 Announce Type: replace Abstract: Reinforcement learning has demonstrated significant potential in the field of autonomous driving. However, it suffers from defects such as training

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Explainable-by-Design Audio Deepfake Detection via Wiener-Hopf Linear Prediction

DGX agent

arXiv:2607.12584v1 Announce Type: cross Abstract: The rapid advancement of synthetic speech generation methods has made audio deepfake detection a critical challenge in multimedia forensics. While rec

model-releasesarxiv-cs-ai

15 Jul 2026

Filtering-out poor-quality images for data preparation

arXiv:2607.12352v1 Announce Type: new Abstract: Filtering noise is a fundamental part of data preparation that enhances image quality for applications such as object segmentation, detection, and recog

agentsarxiv-cs-cv

Hardware

FlashDiff: Efficient Regional Execution and Scheduling for Diffusion Model Serving

arXiv:2607.12121v1 Announce Type: cross Abstract: Diffusion models have become the central backbone for modern image, video, and audio generation, but their efficient service remains a challenge. Unli

hardwarearxiv-cs-lg

From Observation to Insight: Mechanistic World Models and the Quest for Autonomous Discovery

arXiv:2607.12474v1 Announce Type: new Abstract: Recent advances in foundation models have transformed AI for Science, enabling remarkably accurate predictive performance across domains ranging from pr

agentsarxiv-cs-ai

GAINS: Gaussian-based Inverse Rendering from Sparse Multi-View Captures

model-releasesarxiv-cs-cv

arXiv:2512.09925v2 Announce Type: replace Abstract: Recent advances in Gaussian Splatting-based inverse rendering extend Gaussian primitives with shading parameters and physically grounded light trans

Generalization and Memorization in Rectified Flow

arXiv:2603.13421v2 Announce Type: replace-cross Abstract: Generative models based on the Flow Matching objective, particularly Rectified Flow, have emerged as a dominant paradigm for efficient, high-f

Generalized Distribution-Free Semi-Supervised Learning with Risk Rewrite

arXiv:2607.11947v1 Announce Type: cross Abstract: Typical semi-supervised learning (SSL) methods rely on distributional assumptions, and their performance degrades when these are violated. While PNU l

Infra-Swarm: Robust Vision-Based Multi-Robot Swarming via Near-Infrared Spectral Vision

arXiv:2607.12489v1 Announce Type: new Abstract: Distributed swarms typically rely on either active wireless communication or passive vision, and they are frequently hindered by bandwidth constraints o

agentsarxiv-cs-ro

Interpretable and Verifiable Hardware Generation with LLM-Driven Stepwise Refinement

arXiv:2606.19387v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have achieved remarkable success in software development. However, they are susceptible to hallucinations, meanin

agentsarxiv-cs-ai

Jetson-PI: Towards Onboard Real-Time Robot Control via Foresight-Aligned Asynchronous Inference

arXiv:2607.12659v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have achieved impressive performance on diverse embodied tasks. However, deploying VLA models on low-power onboard

Learning an Interpretable Risk Scoring System for Maximizing Decision Net Benefit

arXiv:2604.04241v2 Announce Type: replace Abstract: Risk scoring systems are widely used in high-stakes domains to assist decision-making. However, existing approaches often focus on optimizing predic

Learning-enabled Acceleration of Scenario-based Model Predictive Control

arXiv:2607.12775v1 Announce Type: cross Abstract: Scenario-based model predictive control (SBMPC) is a variant of model predictive control (MPC) that explicitly accounts for uncertainty by optimizing

Learning the Graphical Nature of Symmetries

arXiv:2607.12026v1 Announce Type: cross Abstract: Finite groups are rigid algebraic objects, whose Cayley graphs expose a rich network geometry through which group-theoretic structure can be measured,

Lesion Segmentation in Moderate to Severe Traumatic Brain Injury: An nnU-Net Based Approach with Adaptive Normalization in the AIMS-TBI 2025 Challenge

arXiv:2607.12684v1 Announce Type: new Abstract: The segmentation of lesions in Moderate to Severe Traumatic Brain Injury (msTBI) from T1-weighted MRI presents a significant clinical challenge due to t

Leveraging Prior Knowledge of Diffusion Model for Person Search

arXiv:2510.01841v2 Announce Type: replace Abstract: Person search aims to jointly perform person detection and re-identification by localizing and identifying a query person within a gallery of uncrop

local-aiarxiv-cs-cv

LLM Judges Can Be Too Generous When There Is No Reference Answer

arXiv:2607.12885v1 Announce Type: new Abstract: LLM judges are increasingly being used to evaluate open-ended model responses, often in no-reference settings where a ground-truth answer is unavailable

researcharxiv-cs-cl

MaxSAT-Based Feedback for Guiding Vision-Language Models in Sudoku

arXiv:2607.12711v1 Announce Type: new Abstract: Vision--Language Models (VLMs) have recently demonstrated promising performance on structured visual reasoning tasks, including grid-based puzzles. Howe

Mechanical Analysis of Parachute Suspension Line Deployment with Binding Tapes Using PINN

arXiv:2607.12409v1 Announce Type: new Abstract: Parachutes are widely utilized in aviation, aerospace and lifesaving missions. As the initial stage of parachute deployment, suspension line extraction

MemOps: Benchmarking Lifecycle Memory Operations in Long-Horizon Conversations

arXiv:2607.12893v1 Announce Type: new Abstract: Long-term memory has become a foundational capability for LLM-based agents that accompany users across extended, multi-session interactions. Existing be

MetaView: Monocular Novel View Synthesis with Scale-Aware Implicit Geometry Priors

arXiv:2607.12000v1 Announce Type: new Abstract: Current visual generation models are capable of producing high-quality content, yet they lack a coherent perception of the spatial structure. Existing g

Mirror Horizon: Viable Path Entropy as a Measure of Bounded Reflection

model-releasesarxiv-cs-lg

arXiv:2607.11937v1 Announce Type: new Abstract: Mirror Theory proposes that an intelligent system should be studied not only by what it represents, but by what coherent continuations it can sustain un

Mitigating The Effect of Class Imbalance in Data with Hierarchical and Dependable Structure

arXiv:2607.11994v1 Announce Type: cross Abstract: Classifying cybersecurity vulnerabilities using the Common Weakness Enumeration (CWE) taxonomy is challenging due to extreme class imbalance and stron

Pixel-Level Pavement Distress Assessment Using Instance Segmentation

arXiv:2605.26095v2 Announce Type: replace Abstract: Automated pavement distress assessment requires more than image-level classification or coarse bounding box detection, demanding precise localizatio

local-aiarxiv-cs-cv

PolarBM: Complex-valued Boltzmann Machine for Modeling Audio Signals in Polar and Log-polar Coordinates

arXiv:2607.12417v1 Announce Type: new Abstract: Although vast amounts of data, such as audio signal spectra, are naturally represented using complex numbers, conventional machine learning methods ofte

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PoseAlign: Sculpting Pose-Consistent Meshes via Text-Guided Deformation

arXiv:2607.10560v2 Announce Type: replace-cross Abstract: Mesh deformation, the process of altering the vertex positions of a 3D mesh while preserving its topological structure, is a cornerstone of co

safetyarxiv-cs-cv

Propheticus: Machine Learning Framework for the Development of Predictive Models for Reliable and Secure Software

arXiv:1809.01898v2 Announce Type: replace-cross Abstract: The growing complexity of software calls for innovative solutions that support the deployment of reliable and secure software. Machine Learnin

Applications

Proximity Features: Privacy-Compliant Cold-Start Personalization at Airbnb

arXiv:2607.12246v1 Announce Type: new Abstract: Personalization in two-sided marketplaces relies heavily on user-level features, yet for platforms with infrequent, high-consideration purchases, a larg

applicationsarxiv-cs-lg

Quantification of Credal Uncertainty: A Distance-Based Approach

arXiv:2603.27270v2 Announce Type: replace Abstract: Credal sets, i.e., closed convex sets of probability measures, provide a natural framework to represent aleatoric and epistemic uncertainty in machi

Real-time fall detection based on vision for low-power edge platforms

arXiv:2607.12909v1 Announce Type: cross Abstract: Falling detection is vital for elderly care and intelligent surveillance; however, prevailing vision-based approaches predominantly frame it as static

Real-Time Model Checking for Closed-Loop Robot Reactive Planning

arXiv:2508.19186v2 Announce Type: replace-cross Abstract: Reactive obstacle avoidance methods often cause agents to become trapped in local minima, because they can often only reason one step ahead (i

local-aiarxiv-cs-ai

Applications

ReflectWorld-MM: An Entity-Oriented Multimodal Memory System for Open-Ended Video Streams

arXiv:2607.09759v2 Announce Type: replace-cross Abstract: Building assistants that can continually watch the world, remember what they see, and reason over their accumulated experience is a long-stand

applicationsarxiv-cs-ai

Representation and Reference Selection in Training-Free Synthetic Image Attribution

arXiv:2607.12052v1 Announce Type: cross Abstract: Synthetic image attribution aims at identifying the generator responsible for a given AI-generated image. Training-free reference-based attribution me

Representing and Generating Levels Over Time through Playtrace Reconstructive Partitioning

arXiv:2607.12097v1 Announce Type: new Abstract: Video games are a dynamic medium experienced over time. While there are many Procedural Content Generation (PCG) approaches for generating video game le

Reproducible Reservoir Computing with Thermally Driven Superparamagnets: Controlling Temperature Sensitivity

arXiv:2607.12840v1 Announce Type: cross Abstract: Unconventional computing systems must demonstrate robust performance under real-world environmental conditions to enable practical deployments. We hav

RFMSR: Residual Flow Matching for Image Super-Resolution

arXiv:2607.12753v1 Announce Type: new Abstract: Image super-resolution (ISR) has witnessed remarkable progress with diffusion models and flow matching. The dominant text-to-image (T2I) based approache

RoboDesign1M: A Large-scale Dataset for Robot Design Understanding

model-releasesarxiv-cs-ro

arXiv:2503.06796v2 Announce Type: replace Abstract: Robot design is a complex and time-consuming process that requires specialized expertise. Gaining a deeper understanding of robot design data can en

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Robot Drummer: Learning Rhythmic Skills for Humanoid Drumming

arXiv:2507.11498v3 Announce Type: replace Abstract: Humanoid robots have seen remarkable advances in dexterity, balance, and locomotion, yet their role in expressive domains such as music performance

safetyarxiv-cs-ro

Robust Design of Integrated Sensing and Communication in LEO Satellite Systems

arXiv:2607.12337v1 Announce Type: cross Abstract: With the growing demand for satellite sensing and communication, the limited wireless resources are difficult to support multiple satellite systems. T

Rough Path Signature-Guided Geometry Augmentation for Few-Shot Industrial Surface Defect Detection

arXiv:2607.12245v1 Announce Type: new Abstract: Few-shot industrial defect detection remains difficult for standard supervised detectors, which achieve poor performance on boundary-dominated industria

SheetMind: An End-to-End LLM-Powered Multi-Agent Framework for Spreadsheet Automation

arXiv:2506.12339v2 Announce Type: replace-cross Abstract: We present SheetMind, a modular multi-agent framework powered by large language models (LLMs) for spreadsheet automation via natural language

Signal-Guided Optimization for Machine Unlearning

arXiv:2607.11975v1 Announce Type: cross Abstract: Current machine unlearning methods predominantly rely on global, coarse-grained intervention strategies. They lack precise pilot signals to guide the

SKooP: Symmetric Koopman Predictions for Faster and More Generalizable Legged Robot Locomotion with Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2607.11624v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) algorithms classically suffer from poor sample efficiency. In robotics, a recent line of work has emerged addressi

Sparse Autoencoders for Interpretable Out-of-Distribution Detection

arXiv:2607.12094v1 Announce Type: cross Abstract: Reliable detection of out-of-distribution (OOD) samples is crucial for the safe deployment of machine learning models. Neural networks often produce o

Stochastic Quantum Spiking Neural Networks with Quantum Memory and Local Learning

arXiv:2506.21324v3 Announce Type: replace-cross Abstract: Neuromorphic and quantum computing have recently emerged as promising paradigms for advancing artificial intelligence, each offering complemen

local-aiarxiv-cs-lg

The Geometry of Memorization: Finite-Time Spectral Sensitivity as a Diagnostic for Flow Matching Models

arXiv:2607.12616v1 Announce Type: new Abstract: Continuous-time generative frameworks construct probability paths between base and target domains by optimizing time-dependent velocity fields. While th

The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication

arXiv:2405.11667v2 Announce Type: replace Abstract: Local SGD is a popular optimization method in distributed learning, often outperforming other algorithms in practice, including mini-batch SGD. Desp

The Model Knows Your Project, Not You: Measuring Recognition in LLMs with NameRank

arXiv:2607.12520v1 Announce Type: new Abstract: What a frontier model recalls about a person or tool from its own weights -- before any retrieval step -- often shapes the first description a human see