Search: “research”

A Partition-Based Generating Function for Row-Convex Polyominoes

arXiv:2605.03203v1 Announce Type: cross Abstract: An alternative generating function is proposed to enumerate row-convex polyominoes without internal holes on a discrete grid. The approach is based on

A Perfectly Truthful Calibration Measure

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DGX agent

arXiv:2508.13100v3 Announce Type: replace Abstract: Calibration requires that predictions are conditionally unbiased and, therefore, reliably interpretable as probabilities. A calibration measure quan

researcharxiv-cs-lg

6 May 2026

A Sentence Relation-Based Approach to Sanitizing Malicious Instructions

arXiv:2605.01078v1 Announce Type: cross Abstract: Retrieval-augmented generation and tool-integrated LLM agents increasingly depend on external textual sources. This reliance broadens the available at

A Target-Free Harmonization Method for MRI

arXiv:2605.01282v1 Announce Type: cross Abstract: In MRI, variations in scan parameters, sequence, or hardware can lead to discrepancies in image appearance, even for the same subject. These inconsist

A User-Centric Analysis of Explainability in AI-Based Medical Image Diagnosis

arXiv:2605.02903v1 Announce Type: cross Abstract: In recent years, AI systems in the medical domain have advanced significantly. However, despite outperforming humans, they are rarely used in practice

Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding

arXiv:2505.24791v2 Announce Type: replace Abstract: Discrete normalizing flows are promising generative models with advantages such as analytical log-likelihood computation and end-to-end training. Ho

Adaptive Data Compression and Reconstruction for Memory-Bounded EEG Continual Learning

arXiv:2605.03085v1 Announce Type: new Abstract: Electroencephalography (EEG) signals provide millisecond-level temporal resolution but their analysis is limited by remarkable noise and inter-subject v

Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity

arXiv:2605.03393v1 Announce Type: cross Abstract: Contextual MDPs are powerful tools with wide applicability in areas from biostatistics to machine learning. However, specializing them to offline data

Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning

arXiv:2605.03495v1 Announce Type: new Abstract: We develop graph-based methods for semi-supervised learning based on label propagation on a data similarity graph. When data is abundant or arrive in a

AMSnet-q: Unsupervised Circuit Identification and Performance Labeling for AMS Circuits

arXiv:2605.01404v1 Announce Type: cross Abstract: Analog and mixed-signal (AMS) circuit design remains heavily reliant on expert knowledge. While recent AI-driven automation tools can generate candida

An ERP Study of Recursive Possessive Parsing in ASD Children and Its Cognitive Neuro Mechanisms

arXiv:2605.03447v1 Announce Type: new Abstract: Recursive structures are a core property of human language, yet little is known about how children with autism spectrum disorder (ASD) process complex r

researcharxiv-cs-cl

Analysis and Explainability of LLMs Via Evolutionary Methods

arXiv:2605.02930v1 Announce Type: cross Abstract: Evolutionary methods have long been useful for analysis and explanation in genetics, biology, ecology, and related fields. In this work, we extend the

Analytic Bridge Diffusions for Controlled Path Generation

arXiv:2605.02961v1 Announce Type: new Abstract: Most modern bridge-diffusion methods achieve finite-time transport by specifying an interpolation, Schrodinger-bridge, or stochastic-control objective a

Are we Doomed to an AI Race? Why Self-Interest Could Drive Countries Towards a Moratorium on Superintelligence

arXiv:2605.01297v1 Announce Type: cross Abstract: This paper uses game theory to argue that, contrary to the prevailing view, a moratorium on Artificial Superintelligence (ASI) can be in a state's sel

AsymK-Talker: Real-Time and Long-Horizon Talking Head Generation via Asymmetric Kernel Distillation

arXiv:2605.02948v1 Announce Type: new Abstract: Recent advances in diffusion models have markedly enhanced the visual fidelity of audio-driven talking head generation. Nevertheless, existing methods a

Atomic Fact-Checking Increases Clinician Trust in Large Language Model Recommendations for Oncology Decision Support: A Randomized Controlled Trial

arXiv:2605.03916v1 Announce Type: new Abstract: Question: Does atomic fact-checking, which decomposes AI treatment recommendations into individually verifiable claims linked to source guideline docume

researcharxiv-cs-cl

Attribution-Guided Masking for Robust Cross-Domain Sentiment Classification

arXiv:2605.03091v1 Announce Type: new Abstract: While pre-trained Transformer models achieve high accuracy on in-domain sentiment classification, they frequently experience severe performance degradat

Bandits on graphs and structures

arXiv:2605.03493v1 Announce Type: new Abstract: The goal of this thesis is to investigate the structural properties of certain sequential problems in order to bring the solutions closer to a practical

Behavior-dLDS: A decomposed linear dynamical systems model for neural activity partially constrained by behavior

arXiv:2603.05612v2 Announce Type: replace-cross Abstract: Brain-wide recordings of large-scale networks of neurons now provide an unprecedented view into how the brain drives behavior. However, brain

Beyond Scalars: Evaluating and Understanding LLM Reasoning via Geometric Progress and Stability

arXiv:2603.10384v2 Announce Type: replace Abstract: Evaluating LLM reliability via scalar probabilities often fails to capture the structural dynamics of reasoning. We introduce TRACED, a framework th

BiMind: A Dual-Head Reasoning Model with Attention-Geometry Adapter for Incorrect Information Detection

arXiv:2604.06022v2 Announce Type: replace Abstract: Incorrect information poses significant challenges by disrupting content veracity and integrity, yet most detection approaches struggle to jointly b

researcharxiv-cs-cl

Boundary-Aware Uncertainty Quantification for Wildfire Spread Prediction

arXiv:2605.03148v1 Announce Type: new Abstract: Reliable wildfire spread prediction is vital for risk-aware emergency planning, yet most deep learning models lack principled uncertainty quantification

Caliper-in-the-Loop: Black-Box Optimization for Hyperledger Fabric Performance Tuning

arXiv:2605.02690v1 Announce Type: cross Abstract: Hyperledger Fabric performance depends on many interacting configuration parameters, making manual tuning difficult. We study automated throughput tun

Can Blockchains Reliably Train Machine Learning Models?

arXiv:2307.07066v2 Announce Type: replace-cross Abstract: Large proof of work (PoW) networks allow anyone to earn rewards by running computation-intensive hash puzzles for profit, yet they typically c

Can Multimodal Large Language Models Understand Pathologic Movements? A Pilot Study on Seizure Semiology

arXiv:2605.03352v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated robust capabilities in recognizing everyday human activities, yet their potential for analyzi

Cascade Token Selection for Transformer Attention Acceleration

arXiv:2605.03110v1 Announce Type: new Abstract: A method is presented for reducing the cost of representative token selection in transformer attention layers by exploiting the coherence of the represe

CellxPert: Inference-Time MCMC Steering of a Multi-Omics Single-Cell Foundation Model for In-Silico Perturbation

arXiv:2605.00930v1 Announce Type: cross Abstract: In this work, we introduce CellxPert, a scalable multimodal foundation model that unifies single-cell and spatial multi-omics within a common represen

Certified Purity for Cognitive Workflow Executors: From Static Analysis to Cryptographic Attestation

arXiv:2605.01037v2 Announce Type: cross Abstract: We present a certified purity architecture that converts governance enforcement in cognitive workflow systems from a runtime convention into a structu

CLAPS: Aleatoric-Epistemic Scaling via Last-Layer Laplace for Conformal Regression

arXiv:2512.01384v4 Announce Type: replace Abstract: Conformal regression provides finite-sample marginal coverage, but it does not by itself determine how interval width should adapt across heterogene

Client-Conditional Federated Learning via Local Training Data Statistics

arXiv:2603.11307v2 Announce Type: replace Abstract: Federated learning (FL) under data heterogeneity remains challenging: existing methods either ignore client differences (FedAvg), require costly clu

Co-Generative De Novo Functional Protein Design

arXiv:2605.00948v1 Announce Type: cross Abstract: De novo functional protein design aims to generate protein sequences that realize specified biochemical functions without relying on evolutionary temp

Code World Model Preparedness Report

arXiv:2605.00932v1 Announce Type: cross Abstract: This report documents the preparedness assessment of Code World Model (CWM), a model for code generation and reasoning about code from Meta. We conduc

Complex Equation Learner: Rational Symbolic Regression with Gradient Descent in Complex Domain

arXiv:2605.03841v1 Announce Type: new Abstract: Symbolic regression aims to discover interpretable equations from data, yet modern gradient-based methods fail for operators that introduce singularitie

Conditional Diffusion Sampling

arXiv:2605.04013v1 Announce Type: cross Abstract: Sampling from unnormalized multimodal distributions with limited density evaluations remains a fundamental challenge in machine learning and natural s

Conditions for well-posed color recovery in scattering media

arXiv:2605.03837v1 Announce Type: new Abstract: Recovering scene color from images captured in scattering media is a fundamental inverse problem in optical imaging. Yet the problem is intrinsically il

Context-Aware Wireless Token Communication via Joint Token Masking and Detection

arXiv:2605.02123v1 Announce Type: cross Abstract: The increasing use of token-based representations in language-driven applications has motivated wireless token communication, where tokens are treated

Controllable and Verifiable Process Data Synthesis for Process Reward Models

arXiv:2605.02395v1 Announce Type: new Abstract: Process reward models (PRMs) rely on high-quality process supervision data, yet existing construction methods often provide limited control over error l

CoVSpec: Efficient Device-Edge Co-Inference for Vision-Language Models via Speculative Decoding

arXiv:2605.02218v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated strong capabilities in multimodal perception and reasoning. However, deploying large VLMs on mobile devi

DARTH-PUM: A Hybrid Processing-Using-Memory Architecture

arXiv:2602.16075v2 Announce Type: replace-cross Abstract: Analog processing-using-memory (PUM; a.k.a. in-memory computing) makes use of electrical interactions inside memory arrays to perform bulk mat

Data driven approach for Outdoor Channel Prediction in 5G and Beyond

arXiv:2605.01777v1 Announce Type: cross Abstract: An evolution of Wireless Communications towards 5G and beyond provides improved user experience in terms of quality of services. Understanding and est

DeRelayL: Sustainable Decentralized Relay Learning

arXiv:2605.02935v1 Announce Type: new Abstract: In the era of big data, large-scale machine learning models have revolutionized various fields, driving significant advancements. However, large-scale m

deSEO: Physics-Aware Dataset Creation for High-Resolution Satellite Image Shadow Removal

arXiv:2605.03610v1 Announce Type: new Abstract: Shadows cast by terrain and tall structures remain a major obstacle for high-resolution satellite image analysis, degrading classification, detection, a

Diffusion Masked Pretraining for Dynamic Point Cloud

arXiv:2605.03639v1 Announce Type: new Abstract: Dynamic point cloud pretraining is still dominated by masked reconstruction objectives. However, these objectives inherit two key limitations. Existing

Discover Fast Power Allocation Solution for Multi-Target Tracking via AlphaEvolve Evolution

arXiv:2605.01794v1 Announce Type: cross Abstract: Efficient radar resource allocation is a fundamental yet computationally challenging problem, as optimal solutions typically require iterative optimiz

Disease Is a Spectral Perturbation

arXiv:2605.02949v1 Announce Type: new Abstract: We propose a novel method of understanding disease transformation from a healthy baseline with biomarker-level explainability. By modeling the biomarker

Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding

arXiv:2605.02290v1 Announce Type: new Abstract: Distilling large reasoning models is essential for making Long-CoT reasoning practical, as full-scale inference remains computationally prohibitive. Exi

Distributed Learning with Adversarial Gradient Perturbations

arXiv:2605.03313v1 Announce Type: new Abstract: Privacy concerns in distributed learning often lead clients to return intentionally altered gradient information. We consider the problem of learning co

Distribution-Free Pretraining of Classification Losses via Evolutionary Dynamics

arXiv:2605.03722v1 Announce Type: new Abstract: We propose Evolutionary Dynamic Loss (EDL), a framework that learns a transferable classification loss in the probability space using unlimited syntheti