Search: “papers”

AGNT2: Autonomous Agent Economies on Interaction-Optimized Layer 2 Infrastructure

arXiv:2604.21129v1 Announce Type: cross Abstract: Current blockchain Layer 2 solutions, including Optimism, Arbitrum, zkSync, and their derivatives, optimize for human-initiated financial transactions

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Local Ai

an interpretable vision transformer framework for automated brain tumor classification

DGX agent

arXiv:2604.21311v1 Announce Type: new Abstract: Brain tumors represent one of the most critical neurological conditions, where early and accurate diagnosis is directly correlated with patient survival

local-aiarxiv-cs-cv

24 Apr 2026

Anomaly Detection in Smart Power Grids with Graph-Regularized MS-SVDD: a Multimodal Subspace Learning Approach

arXiv:2502.15793v2 Announce Type: replace Abstract: Anomaly detection in smart power grids is a critical challenge due to the complexity, heterogeneity, and dynamic nature of sensor data streams. Exis

applicationsarxiv-cs-lg

Architectures for Robust Self-Organizing Energy Systems under Information and Control Constraints

arXiv:2604.21529v1 Announce Type: cross Abstract: Applying the concept of controlled self-organization in agent-based Cyber-Physical Energy Systems (CPES) is a promising approach to ensure system robu

AttDiff-GAN: A Hybrid Diffusion-GAN Framework for Facial Attribute Editing

arXiv:2604.21289v1 Announce Type: new Abstract: Facial attribute editing aims to modify target attributes while preserving attribute-irrelevant content and overall image fidelity. Existing GAN-based m

safetyarxiv-cs-cv

Beyond the Frame: Generating 360 Panoramic Videos from Perspective Videos

arXiv:2504.07940v3 Announce Type: replace Abstract: 360{eg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the 'tunnel vision' of standard cameras, their

researcharxiv-cs-cv

BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature

arXiv:2604.21508v1 Announce Type: new Abstract: Protein-ligand bioactivity data published in the literature are essential for drug discovery, yet manual curation struggles to keep pace with rapidly gr

Bounding the Black Box: A Statistical Certification Framework for AI Risk Regulation

arXiv:2604.21854v1 Announce Type: new Abstract: Artificial intelligence now decides who receives a loan, who is flagged for criminal investigation, and whether an autonomous vehicle brakes in time. Go

Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models

arXiv:2604.20994v1 Announce Type: cross Abstract: The growth of agentic AI has drawn significant attention to function calling Large Language Models (LLMs), which are designed to extend the capabiliti

C-SHAP for time series: An approach to high-level temporal explanations

arXiv:2504.11159v2 Announce Type: replace Abstract: In high-stakes domains, such as healthcare and industry, the explainability of AI-based decision-making has become crucial. Without insight into mod

CaST-POI: Candidate-Conditioned Spatiotemporal Modeling for Next POI Recommendation

arXiv:2604.20845v1 Announce Type: cross Abstract: Next Point-of-Interest (POI) recommendation plays a crucial role in location-based services by predicting users' future mobility patterns. Existing me

Causal Disentanglement for Full-Reference Image Quality Assessment

arXiv:2604.21654v1 Announce Type: cross Abstract: Existing deep network-based full-reference image quality assessment (FR-IQA) models typically work by performing pairwise comparisons of deep features

researcharxiv-cs-ai

Cognitive Amplification vs Cognitive Delegation in Human-AI Systems: A Metric Framework

arXiv:2603.18677v2 Announce Type: replace-cross Abstract: Artificial intelligence is increasingly embedded in human decision making. In some cases, it enhances human reasoning. In others, it fosters e

Conjecture and Inquiry: Quantifying Software Performance Requirements via Interactive Retrieval-Augmented Preference Elicitation

arXiv:2604.21380v1 Announce Type: cross Abstract: Since software performance requirements are documented in natural language, quantifying them into mathematical forms is essential for software enginee

CSC: Turning the Adversary's Poison against Itself

arXiv:2604.21416v1 Announce Type: cross Abstract: Poisoning-based backdoor attacks pose significant threats to deep neural networks by embedding triggers in training data, causing models to misclassif

DenoiseRank: Learning to Rank by Diffusion Models

arXiv:2604.20852v1 Announce Type: cross Abstract: Learning to rank (LTR) is one of the core tasks in Machine Learning. Traditional LTR models have made great progress, but nearly all of them are imple

Tutorials

Design, Modelling and Experimental Evaluation of a Tendon-driven Wrist Abduction-Adduction Mechanism for an upper limb exoskeleton

arXiv:2604.20893v1 Announce Type: new Abstract: Wrist exoskeletons play a vital role in rehabilitation and assistive applications, yet conventional actuation mechanisms such as electric motors or pneu

tutorialsarxiv-cs-ro

Do LLMs Overthink Basic Math Reasoning? Benchmarking the Accuracy-Efficiency Tradeoff in Language Models

model-releasesarxiv-cs-cl

arXiv:2507.04023v3 Announce Type: replace Abstract: Large language models (LLMs) achieve impressive performance on complex mathematical benchmarks yet sometimes fail on basic math reasoning while gene

Droplet-LNO: Physics-Informed Laplace Neural Operators for Accurate Prediction of Droplet Spreading Dynamics on Complex Surfaces

arXiv:2604.20993v1 Announce Type: new Abstract: Spreading of liquid droplets on solid substrates constitutes a classic multiphysics problem with widespread applications ranging from inkjet printing, s

Drug Synergy Prediction via Residual Graph Isomorphism Networks and Attention Mechanisms

arXiv:2604.21473v1 Announce Type: cross Abstract: In the treatment of complex diseases, treatment regimens using a single drug often yield limited efficacy and can lead to drug resistance. In contrast

EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization

arXiv:2411.00171v2 Announce Type: replace Abstract: To avoid myopic behavior, multi-step lookahead Bayesian optimization (BO) algorithms consider the sequential nature of BO and have demonstrated prom

Effects of Swarm Size Variability on Operator Workload

arXiv:2604.21707v1 Announce Type: new Abstract: Real-world deployments of human--swarm teams depend on balancing operator workload to leverage human strengths without inducing overload. A key challeng

agentsarxiv-cs-ro

Enhancing Online Recruitment with Category-Aware MoE and LLM-based Data Augmentation

arXiv:2604.21264v1 Announce Type: new Abstract: Person-Job Fit (PJF) is a critical component for online recruitment. Existing approaches face several challenges, particularly in handling low-quality j

researcharxiv-cs-ai

ERA: Evidence-based Reliability Alignment for Honest Retrieval-Augmented Generation

arXiv:2604.20854v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds language models in factual evidence but introduces critical challenges regarding knowledge conflicts betw

Evaluation of Automatic Speech Recognition Using Generative Large Language Models

arXiv:2604.21928v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) is traditionally evaluated using Word Error Rate (WER), a metric that is insensitive to meaning. Embedding-based sema

researcharxiv-cs-cl

Tutorials

Exploring Continual Fine-Tuning for Enhancing Language Ability in Large Language Model

arXiv:2410.16006v3 Announce Type: replace Abstract: A common challenge towards the adaptability of Large Language Models (LLMs) is their ability to learn new languages over time without hampering the

tutorialsarxiv-cs-cl

Fairness under uncertainty in sequential decisions

arXiv:2604.21711v1 Announce Type: cross Abstract: Fair machine learning (ML) methods help identify and mitigate the risk that algorithms encode or automate social injustices. Algorithmic approaches al

Finding Meaning in Embeddings: Concept Separation Curves

arXiv:2604.21555v1 Announce Type: new Abstract: Sentence embedding techniques aim to encode key concepts of a sentence's meaning in a vector space. However, the majority of evaluation approaches for s

researcharxiv-cs-cl

Fine-Tuning Regimes Define Distinct Continual Learning Problems

arXiv:2604.21927v1 Announce Type: new Abstract: Continual learning (CL) studies how models acquire tasks sequentially while retaining previously learned knowledge. Despite substantial progress in benc

From Tokens to Concepts: Leveraging SAE for SPLADE

arXiv:2604.21511v1 Announce Type: cross Abstract: Learned Sparse IR models, such as SPLADE, offer an excellent efficiency-effectiveness tradeoff. However, they rely on the underlying backbone vocabula

researcharxiv-cs-cl

Geometric Characterisation and Structured Trajectory Surrogates for Clinical Dataset Condensation

arXiv:2604.21638v1 Announce Type: new Abstract: Dataset condensation constructs compact synthetic datasets that retain the training utility of large real-world datasets, enabling efficient model devel

Local Ai

Gmd: Gaussian mixture descriptor for pair matching of 3D fragments

arXiv:2604.21519v1 Announce Type: new Abstract: In the automatic reassembly of fragments acquired using laser scanners to reconstruct objects, a crucial step is the matching of fractured surfaces. In

local-aiarxiv-cs-cv

GS-Quant: Granular Semantic and Generative Structural Quantization for Knowledge Graph Completion

arXiv:2604.21649v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown immense potential in Knowledge Graph Completion (KGC), yet bridging the modality gap between continuous graph em

researcharxiv-cs-ai

HiCrew: Hierarchical Reasoning for Long-Form Video Understanding via Question-Aware Multi-Agent Collaboration

arXiv:2604.21444v1 Announce Type: new Abstract: Long-form video understanding remains fundamentally challenged by pervasive spatiotemporal redundancy and intricate narrative dependencies that span ext

How VLAs (Really) Work In Open-World Environments

arXiv:2604.21192v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) have been extensively used in robotics applications, achieving great success in various manipulation problems. Mo

Hybrid Deep Learning Approach for Coupled Demand Forecasting and Supply Chain Optimization

arXiv:2604.21567v1 Announce Type: cross Abstract: Supply chain resilience and efficiency are vital in industries characterized by volatile demand and uncertain supply, such as textiles and personal pr

HyperAdapt: Simple High-Rank Adaptation

arXiv:2509.18629v3 Announce Type: replace-cross Abstract: Foundation models excel across diverse tasks, but adapting them to specialized applications often requires fine-tuning, an approach that is me

Hyperloop Transformers

model-releasesarxiv-cs-cl

arXiv:2604.21254v1 Announce Type: cross Abstract: LLM architecture research generally aims to maximize model quality subject to fixed compute/latency budgets. However, many applications of interest su

InfiniPipe: Elastic Pipeline Parallelism for Efficient Variable-Length Long-Context LLM Training

arXiv:2509.21275v3 Announce Type: replace-cross Abstract: Long context training is crucial for LLM's context extension. Existing schemes, such as sequence parallelism, incur substantial communication

Integrated packing, placement, scheduling, and routing of personalized production: a pharmaceutical Industry 4.0 use-case with a planar transport system

arXiv:2604.21029v1 Announce Type: cross Abstract: The recent emergence of planar transport systems necessitates re-evaluation of Flexible Manufacturing Systems (FMS) to address the simultaneous schedu

Interpretable Quantile Regression by Optimal Decision Trees

arXiv:2604.21042v1 Announce Type: new Abstract: The field of machine learning is subject to an increasing interest in models that are not only accurate but also interpretable and robust, thus allowing

researcharxiv-cs-lg

Tutorials

JEPAMatch: Geometric Representation Shaping for Semi-Supervised Learning

arXiv:2604.21046v1 Announce Type: new Abstract: Semi-supervised learning has emerged as a powerful paradigm for leveraging large amounts of unlabeled data to improve the performance of machine learnin

tutorialsarxiv-cs-lg

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems

arXiv:2508.10177v3 Announce Type: replace Abstract: Recent Large Language Model (LLM)-based AutoML systems demonstrate impressive capabilities but face significant limitations such as constrained expl

LAF-Based Evaluation and UTTL-Based Learning Strategies with MIATTs

arXiv:2604.20944v1 Announce Type: cross Abstract: In many real-world machine learning (ML) applications, the true target cannot be precisely defined due to ambiguity or subjectivity information. To ad

Language-Conditioned Safe Trajectory Generation for Spacecraft Rendezvous

arXiv:2512.09111v3 Announce Type: replace-cross Abstract: Reliable real-time trajectory generation is essential for future autonomous spacecraft. While recent progress in nonconvex guidance and contro

LatRef-Diff: Latent and Reference-Guided Diffusion for Facial Attribute Editing and Style Manipulation

arXiv:2604.21279v1 Announce Type: new Abstract: Facial attribute editing and style manipulation are crucial for applications like virtual avatars and photo editing. However, achieving precise control

researcharxiv-cs-cv

Linear Image Generation by Synthesizing Exposure Brackets

arXiv:2604.21008v1 Announce Type: new Abstract: The life of a photo begins with photons striking the sensor, whose signals are passed through a sophisticated image signal processing (ISP) pipeline to

researcharxiv-cs-cv

Local Neighborhood Instability in Parametric Projections: Quantitative and Visual Analysis

arXiv:2604.21617v1 Announce Type: new Abstract: Parametric projections let analysts embed new points in real time, but input variations from measurement noise or data drift can produce unpredictable s

safetyarxiv-cs-cv