Search: “papers”

Balancing Fairness, Privacy, and Accuracy: A Multitask Adversarial Framework for Centralized Data-Driven Systems

arXiv:2605.24458v1 Announce Type: cross Abstract: The integration of fairness and privacy in centralized data-driven applications is critical, especially as these systems increasingly influence sector

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

BandVQ: Band-Wise Vector-Quantized EEG Foundation Model

DGX agent

arXiv:2605.24921v1 Announce Type: new Abstract: A central challenge in electroencephalography (EEG) foundation modeling is learning transferable representations across recordings with diverse tasks, m

researcharxiv-cs-lg

26 May 2026

Benchmarking non-conformity score functions in conformal prediction

arXiv:2605.24983v1 Announce Type: new Abstract: Conformal prediction is a useful and versatile alternative to model calibration in machine learning classification. It replaces single-class prediction

Beyond Control-Flow: Integrating the Resource Perspective into Multi-Collaborative Process Modeling from Text

arXiv:2605.24546v1 Announce Type: new Abstract: Process modeling is a sub-domain of Business Process Management (BPM) focused on the translation of process artifacts into formal models. This task trad

Agents

Beyond Predefined Learning Objects: A Thinking-Learning Interaction Model for Up-to-Date Autonomous Robot Learning

arXiv:2605.23987v1 Announce Type: new Abstract: Autonomous robots operating in open and changing environments cannot always rely on predefined inputs, outputs, and action routines. Although existing l

agentsarxiv-cs-ai

Beyond Query Memorization: Large Language Model Routing with Query Decomposition and Historical Matching

arXiv:2605.25558v1 Announce Type: new Abstract: Optimizing the trade-off among predictive performance and computational cost is a central focus in the deployment of Large Language Models (LLMs). Curre

Beyond Summaries: Structure-Aware Labeling of Code Changes with Large Language Models

arXiv:2605.26100v1 Announce Type: cross Abstract: Code review is a critical practice in software engineering, yet the growing scale and frequency of code patches in modern projects, together with the

Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization in Overparameterized ResNets

arXiv:2403.04545v3 Announce Type: replace Abstract: Scaling factors in residual branches have emerged as a prevalent method for boosting neural network performance, especially in normalization-free ar

applicationsarxiv-cs-lg

Byzantine-Robust Federated Learning with Learnable Aggregation Weights

arXiv:2511.03529v2 Announce Type: replace Abstract: Federated Learning (FL) enables clients to collaboratively train a global model without sharing their private data. However, the presence of malicio

CAFD: Concept-Aware DNN Fault Detection using VLMs

arXiv:2605.24008v1 Announce Type: new Abstract: Fault detection for Deep Neural Networks (DNNs) has received increasing attention in recent years. While more advanced hybrid approaches have been propo

applicationsarxiv-cs-lg

CALIBURN: A Regime-Sensitivity Study of Operationally Calibrated Streaming Intrusion Detection

arXiv:2605.24696v1 Announce Type: cross Abstract: Streaming network intrusion detection systems must process flows continuously while keeping memory bounded, but most current methods leave alerting th

applicationsarxiv-cs-lg

Capability and Robustness Cannot Both Be Free: An Information-Theoretic Bound for Vision-Language-Action Models

arXiv:2605.25889v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are increasingly deployed on real robots, where each predicted action is executed and each failure carries a safet

Capture-Calibrate-Coach: A Graph-Based Framework for Knowledge Monitoring Estimation and Adaptive Feedback

arXiv:2605.25419v1 Announce Type: new Abstract: Effective learning support requires understanding not only what learners know but also how accurately they perceive their own understanding. This metaco

Clustering based on Stochastic Dominance with application for risk averters and risk seekers

arXiv:2605.24422v1 Announce Type: cross Abstract: Stochastic Dominance (SD) theory provides a rigorous framework for selecting superior assets tailored to the asset allocation needs of investors with

Code2UML: Agentic LLMs with context engineering for scalable software visualization

arXiv:2605.24453v1 Announce Type: cross Abstract: Large Language Model (LLM)-based code analysis tools are adopted to automate software documentation tasks. However, the scalability of these approache

Local Ai

Continuous-Depth Field Theory for Transformer Patching and Mechanistic Interpretability

arXiv:2605.25225v1 Announce Type: cross Abstract: Mechanistic interpretability often uses activation patching, causal tracing, path patching, and steering directions to reveal behaviorally meaningful

local-aiarxiv-cs-ai

Contractual Skills: A GovernSpec Design Framework for Enterprise AI Agents

arXiv:2605.22634v2 Announce Type: replace-cross Abstract: Skills have become a practical packaging mechanism for agent instructions, workflows, scripts, and reference materials. In enterprise settings

Convex-Neural RRT*: Fast and Reliable Learning-Guided Sampling for High-Quality Robot Path Planning

model-releasesarxiv-cs-lg

arXiv:2605.25006v1 Announce Type: cross Abstract: Sampling-based algorithms for robot path planning offer probabilistic completeness and strong empirical convergence properties across environments wit

Coupled Variational Reinforcement Learning for Language Model General Reasoning

arXiv:2512.12576v3 Announce Type: replace-cross Abstract: While reinforcement learning has achieved impressive progress in language model reasoning, it is constrained by the requirement for verifiable

Cross-Stage Attention Multi-Expert Network for Radiologist-Inspired Breast Ultrasound Diagnosis

arXiv:2605.25518v1 Announce Type: cross Abstract: Breast ultrasound imaging is an important noninvasive method for early breast cancer diagnosis, but automatic benign/malignant classification remains

DarkForest: Less Talk, Higher Accuracy for Multi-Agent LLMs

arXiv:2605.25188v1 Announce Type: new Abstract: Multi-agent LLM systems improve reasoning by combining outputs from multiple agents, but interaction-heavy methods can introduce error propagation and h

Data-Driven Optimization of Tactile Sensor Configurations for Efficient Dexterous Manipulation

arXiv:2409.20473v3 Announce Type: replace Abstract: Tactile sensing is critical for learning-based dexterous manipulation, yet principled guidelines for sensor placement remain largely absent. While d

safetyarxiv-cs-ro

DBPnet: Damper Characteristics-Based Bayesian Physics-Informed Neural Network for Wheel Load Estimation

arXiv:2605.24860v1 Announce Type: cross Abstract: Advanced driver assistance systems (ADAS) play an important role in modern automotive intelligence, significantly enhancing vehicle safety and stabili

DeIDClinic: A Risk-Aware Pseudonymization Framework for Clinical Text De-identification and Re-identification Risk Assessment

arXiv:2410.01648v2 Announce Type: replace Abstract: The increasing availability of sensitive textual data has created an urgent need for robust de-identification methods that enable compliant data sha

applicationsarxiv-cs-cl

Delayed Assignments in Online Non-Centroid Clustering with Stochastic Arrivals

arXiv:2601.16091v2 Announce Type: replace-cross Abstract: Clustering is a fundamental problem, aiming to partition a set of elements, like agents or data points, into clusters such that elements in th

Delta Energy: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization

arXiv:2510.11296v3 Announce Type: replace-cross Abstract: Recent approaches for vision-language models (VLMs) have shown remarkable success in achieving fast downstream adaptation. When applied to rea

Tutorials

Demystifying the Mythos or Disrupting Bugonomics? From Zero-Day Asymmetry to Defender Remediation Throughput

arXiv:2605.24632v1 Announce Type: cross Abstract: Recent demonstrations of large language models producing candidate and confirmed vulnerabilities in production software have renewed the narrative tha

tutorialsarxiv-cs-ai

Discrete diffusion samplers and bridges: Off-policy algorithms and applications in latent spaces

arXiv:2602.05961v2 Announce Type: replace Abstract: Sampling from a distribution p(x) propto e^{-E(x)} known up to a normalising constant is an important and challenging problem in statistics. Recent

Disentangled Double Machine Learning for Accurate Causal Effect Estimation

arXiv:2605.24808v1 Announce Type: cross Abstract: Confounding bias is a key challenge in causal effect estimation from observational data. Double Machine Learning (DML) addresses this issue by estimat

Double Self-weighted Multi-view Clustering via Adaptive View Fusion

arXiv:2011.10396v3 Announce Type: replace-cross Abstract: Multi-view clustering has been applied in many real-world applications where original data often contain noises. Some graph-based multi-view c

applicationsarxiv-cs-ai

DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting

arXiv:2601.21726v2 Announce Type: replace Abstract: Deep time series models are vulnerable to noisy data ubiquitous in real-world applications. Existing robustness strategies either prune data or rely

Local Ai

DTO: a Differentiable Training Objective for Effective Counterfactual Story Rewriting

arXiv:2605.24885v1 Announce Type: new Abstract: Counterfactual story rewriting is a natural language processing task that requires updating an existing story to reflect a chosen alternative event, yet

local-aiarxiv-cs-cl

Efficient Imputation for Patch-based Missing Single-cell Data via Cluster-regularized Optimal Transport

arXiv:2601.14653v2 Announce Type: replace Abstract: Missing data in single-cell sequencing datasets poses significant challenges for extracting meaningful biological insights. However, existing imputa

Emission-Aware Reinforcement Learning for Sustainable Electric Vehicle Charging and Carbon Dioxide Reduction Under Varying Renewable Penetration

arXiv:2605.24543v1 Announce Type: new Abstract: The rapid growth of Electric Vehicle (EV) adoption challenges power distribution networks through peak load spikes, voltage instability, and transformer

EVA: Accelerating LLM Decoding via an Efficient Vector Quantization Architecture

arXiv:2605.24144v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved impressive performance across diverse domains but remain inefficient during the autoregressive decoding pha

Explainable Attention-Guided Stacked Graph Neural Networks for Malware Detection

arXiv:2508.09801v3 Announce Type: replace-cross Abstract: Malware detection in modern computing environments demands models that are not only accurate but also interpretable and robust to evasive tech

Local Ai

ExplainReduce: Generating global explanations from many local explanations

arXiv:2502.10311v3 Announce Type: replace-cross Abstract: Most commonly used non-linear machine learning methods are closed-box models, uninterpretable to humans. The field of explainable artificial i

local-aiarxiv-cs-ai

Factored Latent Action World Models

arXiv:2602.16229v2 Announce Type: replace Abstract: Learning latent actions from action-free video has emerged as a powerful paradigm for scaling up controllable world model learning. Latent actions p

FLINGO -- Instilling ASP Expressiveness into Linear Integer Constraints

arXiv:2602.09620v2 Announce Type: replace Abstract: Constraint Answer Set Programming (CASP) is a hybrid paradigm that enriches Answer Set Programming (ASP) with numerical constraint processing, a cru

applicationsarxiv-cs-ai

From Accounting to Coordination: A Virtual Water-Aware Electricity-Computation-Water Nexus Framework for Data Center Dispatch

arXiv:2605.25854v1 Announce Type: new Abstract: The expansion of data centers (DCs) drives a sustained increase in electricity demand and associated water withdrawals at generation sites. These withdr

From Reasoning to Code: GRPO Optimization for Underrepresented Languages

arXiv:2506.11027v3 Announce Type: replace-cross Abstract: Generating accurate and executable code using Large Language Models (LLMs) remains a significant challenge for underrepresented programming la

FrontierOR: Benchmarking LLMs' Capacity for Efficient Algorithm Design in Large-Scale Optimization

arXiv:2605.25246v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for optimization modeling and solver-code generation, yet practical operations research and optimizat

Fundamental Limitation in Explaining AI

arXiv:2605.24727v1 Announce Type: new Abstract: While large-scale models such as LLMs and diffusion models have achieved practical success, public institutions have emphasized the importance of explai

GDformer: Going Beyond Subsequence Isolation for Multivariate Time Series Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2501.18196v3 Announce Type: replace Abstract: Unsupervised anomaly detection of multivariate time series is a challenging task, given the requirements of deriving a compact detection criterion w

Global Convergence of Wasserstein Policy Gradient for Entropy-Regularized Reinforcement Learning

arXiv:2605.26078v1 Announce Type: new Abstract: Wasserstein policy gradient (WPG) is a policy optimization method for reinforcement learning (RL) that exploits the optimal-transport geometry of action

Go witheFlow: Real-time Emotion Driven Audio Effects Modulation

arXiv:2510.02171v3 Announce Type: replace-cross Abstract: Music performance is a distinctly human activity, intrinsically linked to the performer's ability to convey, evoke, or express emotion. Machin

Grammatically-Guided Sparse Attention for Efficient and Interpretable Transformers

arXiv:2605.24518v1 Announce Type: cross Abstract: The quadratic complexity of self-attention in Transformer models remains a significant bottleneck for processing long sequences and deploying large la

GreenSeg: Ground Segmentation Algorithm for Agricultural Robots in Mediterranean Greenhouses using RGB-D Point Clouds

model-releasesarxiv-cs-ro

arXiv:2605.25279v1 Announce Type: new Abstract: Greenhouse agriculture in the Mediterranean region faces significant automation challenges due to its unique structural and environmental constraints. T