Search: “evaluation”

Complete Cyclic Subtask Graphs for Tool-Using LLM Agents: Flexibility, Cost, and Bottlenecks in Multi-Agent Workflows

arXiv:2604.22820v1 Announce Type: cross Abstract: Long-horizon tool-using tasks sometimes benefit from revisiting earlier subtasks for recovery and exploration, but added multi-agent workflow flexibil

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Computer Vision-Based Early Detection of Container Loss at Sea

DGX agent

arXiv:2604.24193v1 Announce Type: new Abstract: Containerised shipping underpins global trade, yet container loss at sea remains a persistent safety, environmental, and economic challenge. Despite com

safetyarxiv-cs-cv

28 Apr 2026

Conflict-Aware Harmonized Rotational Gradient for Multiscale Kinetic Regimes

arXiv:2604.24745v1 Announce Type: new Abstract: In this paper, we propose a harmonized rotational gradient method, termed HRGrad, for simultaneously tackling multiscale time-dependent kinetic problems

safetyarxiv-cs-lg

Agents

Constraint-Guided Multi-Agent Decompilation for Executable Binary Recovery

arXiv:2604.23940v1 Announce Type: cross Abstract: Decompilation -- recovering source code from compiled binaries -- is essential for security analysis, malware reverse engineering, and legacy software

agentsarxiv-cs-ai

Context-Integrated Adversarial Learning for Predictive Modelling of Stock Price Dynamics

arXiv:2604.22801v1 Announce Type: cross Abstract: It is a challenging task to forecast equity prices in fast moving financial markets as this becomes even more difficult when the predictive signal is

researcharxiv-cs-lg

CorpusQA: A 10 Million Token Benchmark for Corpus-Level Analysis and Reasoning

arXiv:2601.14952v2 Announce Type: replace-cross Abstract: While large language models now handle million-token contexts, their capacity for reasoning across entire document repositories remains largel

Coverage-Based Calibration for Post-Training Quantization via Weighted Set Cover over Outlier Channels

model-releasesarxiv-cs-lg

arXiv:2604.24008v1 Announce Type: new Abstract: Post-Training Quantization (PTQ) compresses large language models to low bit-widths using a small calibration set, and its quality depends strongly on w

Cross-Course Generalizability of SRL-Aligned Predictive Models Using Digital Learning Traces

arXiv:2604.22812v1 Announce Type: cross Abstract: STEM dropout rates remain high at universities, particularly in computer science programs with theory-intensive courses. Digital learning environments

tutorialsarxiv-cs-lg

CT-Guided Spatially-varying Regularization for Voxel-Wise Deformable Whole-Body PET Registration

arXiv:2604.22905v1 Announce Type: cross Abstract: Whole-body Positron Emission Tomography (PET) registration is essential for multi-parametric tumor characterization and assessment of metastatic disea

safetyarxiv-cs-ai

CyberCane: Neuro-Symbolic RAG for Privacy-Preserving Phishing Detection with Formal Ontology Reasoning

arXiv:2604.23563v1 Announce Type: cross Abstract: Privacy-critical domains require phishing detection systems that satisfy contradictory constraints: near-zero false positives to prevent workflow disr

applicationsarxiv-cs-ai

DARC-CLIP: Dynamic Adaptive Refinement with Cross-Attention for Meme Understanding

model-releasesarxiv-cs-cl

arXiv:2604.23214v1 Announce Type: new Abstract: Memes convey meaning through the interaction of visual and textual signals, often combining humor, irony, and offense in subtle ways. Detecting harmful

Decentralized Heterogeneous Multi-Robot Collaborative Exploration for Indoor and Outdoor 3D Environments

arXiv:2604.23693v1 Announce Type: new Abstract: Heterogeneous multi-robot systems feature significant adaptability for complex environments. However, effective collaboration that fully exploits the ro

researcharxiv-cs-ro

Decoding the mechanisms of the Hattrick football manager game using Bayesian network structure learning

arXiv:2504.09499v2 Announce Type: replace-cross Abstract: Hattrick is a free web-based probabilistic football manager game with over 200,000 users competing for titles at national and international le

researcharxiv-cs-ai

DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting

arXiv:2604.23968v1 Announce Type: cross Abstract: Accurate time series forecasting in scientific domains such as climate modeling, physiological monitoring, and energy systems benefits from both compe

Decoupling Wavelet Sub-bands for Single Source Domain Generalization in Fundus Image Segmentation

arXiv:2603.28463v2 Announce Type: replace Abstract: Domain generalization in fundus imaging is challenging due to variations in acquisition conditions across devices and clinical settings. The inabili

Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics

arXiv:2604.23874v1 Announce Type: cross Abstract: Deep learning approaches have shown remarkable promise in turbulence closure modeling for large eddy simulations (LES). The differentiable physics par

tutorialsarxiv-cs-lg

DeepImagine: Learning Biomedical Reasoning via Successive Counterfactual Imagining

arXiv:2604.23054v1 Announce Type: cross Abstract: Predicting the outcomes of prospective clinical trials remains a major challenge for large language models. Prior work has shown that both traditional

Local Ai

DeepSignature: Digitally Signed, Content-Encoding Watermarks for Robust and Transparent Image Authentication

arXiv:2604.23016v1 Announce Type: cross Abstract: AI-powered generative models have significantly expanded the possibilities for editing, manipulating, and creating high-quality images. Particularly,

local-aiarxiv-cs-ai

Defective Task Descriptions in LLM-Based Code Generation: Detection and Analysis

arXiv:2604.24703v1 Announce Type: cross Abstract: Large language models are widely used for code generation, yet they rely on an implicit assumption that the task descriptions are sufficiently detaile

Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing

arXiv:2604.24162v1 Announce Type: cross Abstract: Defending against backdoor attacks in large language models remains a critical practical challenge. Existing defenses mitigate these threats but typic

Deploy DINO with Many-to-Many Association

arXiv:2604.23670v1 Announce Type: new Abstract: Motivated by the limited generalization of supervised image matching models to unseen image domains, we explore the zero-shot deployment of DINO feature

DGHMesh: A Large-scale Dual-radar mmWave Dataset and Generalization-focused Benchmark for Human Mesh Reconstruction

arXiv:2604.22827v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar has shown great potential for contactless, privacy-preserving, and robust human sensing, yet existing mmWave-based human

Differentiable Faithfulness Alignment for Cross-Model Circuit Transfer

model-releasesarxiv-cs-cl

arXiv:2604.24302v1 Announce Type: new Abstract: Mechanistic interpretability has made it possible to localize circuits underlying specific behaviors in language models, but existing methods are expens

DiffuSAM: Diffusion-Based Prompt-Free SAM2 for Few-Shot and Source-Free Medical Image Segmentation

arXiv:2604.24719v1 Announce Type: new Abstract: Segmentation models such as Segment Anything Model (SAM) and SAM2 achieve strong prompt-driven zero-shot performance. However, their training on natural

Discriminator-Guided Adaptive Diffusion for Source-Free Test-Time Adaptation under Image Corruptions

arXiv:2604.23636v1 Announce Type: new Abstract: In this work, we study Source-Free Unsupervised Domain Adaptation under corruption-induced domain shifts, where performance degradation is caused by nat

Don't Pause! Every prediction matters in a streaming video

arXiv:2604.24317v1 Announce Type: new Abstract: Streaming video models should respond the moment an event unfolds, not after the moment has passed. Yet existing online VideoQA benchmarks remain largel

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

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

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

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

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

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

safetyarxiv-cs-ai

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

researcharxiv-cs-ai

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

Agents

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

agentsarxiv-cs-ai

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

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

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

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

Event-based SLAM Benchmark for High-Speed Maneuvers

model-releasesarxiv-cs-ro

arXiv:2604.24033v1 Announce Type: new Abstract: Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution,

EX-FIQA: Leveraging Intermediate Early eXit Representations from Vision Transformers for Face Image Quality Assessment

arXiv:2604.22842v1 Announce Type: new Abstract: Face Image Quality Assessment is crucial for reliable face recognition systems, yet existing Vision Transformer-based approaches rely exclusively on fin

Local Ai

EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT

arXiv:2604.24146v1 Announce Type: new Abstract: Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet the growing scale and complexity of volumetric imagin

local-aiarxiv-cs-cv

Explainable AI for Mental Disorder Detection via Social Media: A survey and outlook

arXiv:2406.05984v2 Announce Type: replace-cross Abstract: Mental health constitutes a complex and pervasive global challenge, affecting millions of lives and often leading to severe consequences. In t

tutorialsarxiv-cs-ai

Extreme bandits

arXiv:2604.24545v1 Announce Type: cross Abstract: In many areas of medicine, security, and life sciences, we want to allocate limited resources to different sources in order to detect extreme values.

safetyarxiv-cs-lg

Local Ai

Factual and Edit-Sensitive Graph-to-Sequence Generation via Graph-Aware Adaptive Noising

arXiv:2604.24104v1 Announce Type: new Abstract: Fine-tuned autoregressive models for graph-to-sequence generation (G2S) often struggle with factual grounding and edit sensitivity. To tackle these issu

local-aiarxiv-cs-cl

FDIM: A Feature-distance-based Generic Video Quality Metric for Versatile Codecs

arXiv:2604.24123v1 Announce Type: new Abstract: Video technology is advancing toward Ultra High Definition (UHD) and High Dynamic Range (HDR), which intensifies the need for higher compression efficie

Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective

arXiv:2604.23267v1 Announce Type: new Abstract: Large language models (LLMs) operate in two fundamental learning modes - fine-tuning (FT) and in-context learning (ICL) - raising key questions about wh

tutorialsarxiv-cs-cl