research

Attention-Guided Layer Selection for Contrastive Decoding in Large Language Models

arXiv:2607.23067v1 Announce Type: cross Abstract: Contrastive decoding methods such as DoLa improve the factuality of Large Language Models (LLMs) by contrasting the output distributions of mature and

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{au}: Learning Touch-Augmented Vision-Language-Action Models from Future Visual Supervision

DGX agent

arXiv:2607.24485v1 Announce Type: new Abstract: Learning the informative tactile representation while effectively adapting it to pretrained Vision-Language-Action (VLA) models remains challenging at b

researcharxiv-cs-ro

28 Jul 2026

AutoCluster, AutoTopicModeling, AutoTrendAnalysis: A Complete AutoML Pipeline for Predicting Emerging Trends

arXiv:2607.22641v1 Announce Type: cross Abstract: Predicting emerging trends is vital for businesses, researchers, and policymakers; yet traditional approaches often lack scalability and adaptability.

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting

arXiv:2605.05540v2 Announce Type: replace Abstract: Fast surrogate modeling for high-dimensional physical dynamics requires more than low short-term error: useful models must roll out efficiently whil

Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram

arXiv:2607.22980v1 Announce Type: new Abstract: Brain-computer interfaces (BCIs) have long sought calibration-free operation, but classifiers are typically benchmarked by discrimination alone, blind t

Benchmarking the Domain Gap: Model Selection Instability Under Domain Shift in Video Capsule Endoscopy

arXiv:2607.22736v1 Announce Type: new Abstract: Video capsule endoscopy (VCE) classification is typically evaluated within a single dataset, yet clinical deployment demands robustness across acquisiti

Beyond Aggregate Risk: Role-Stratified Conformal Risk Control for LLM Tool Calls

arXiv:2607.24343v1 Announce Type: cross Abstract: Language-model agents act through structured tool calls whose arguments carry different risks. Untrusted content may safely influence an email body bu

Beyond Directed Acyclic Graphs: Causal Zeros and Causal Differential Equations

arXiv:2607.22910v1 Announce Type: new Abstract: Pearl's structural causal model (SCM) framework, built on directed acyclic graphs (DAGs) and the do-calculus, is the dominant formal language for causal

Beyond Error-vs-Discard Characteristic: Toward Stable and Reliable Evaluation for Face Image Quality Assessment

arXiv:2607.22752v1 Announce Type: new Abstract: Face Image Quality Assessment (FIQA) aims to estimate the utility of facial images for reliable recognition. The evaluation of FIQA methods is predomina

Bigger or Cheaper? Scale and Quantization Effects on Uncertainty Signals in Vision-Language Models Under Image Degradation

arXiv:2607.24440v1 Announce Type: cross Abstract: Vision-language models (VLMs) deployed on consumer hardware must decide when to answer and when to defer, and that decision depends on having a confid

BioSentinel at EXIST 2026: Soft-Label Optimization with XLM-RoBERTa for Sexism Intent Classification in Memes

arXiv:2607.24137v1 Announce Type: new Abstract: This paper describes the BioSentinel team's participation in EXIST 2026 Task 2.2: Source Intention in Memes, part of the CLEF 2026 evaluation campaign.

Bit-Accurate FPGA Evaluation of Learned Feature Gating in a Fixed-Point Fourier-Feature Automatic Modulation Classifier

arXiv:2607.24568v1 Announce Type: new Abstract: Learned feature reweighting can improve automatic modulation classification (AMC) in software, but the same operation introduces additional arithmetic a

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set

arXiv:2607.23679v1 Announce Type: new Abstract: Recent years have witnessed increasing interests in tackling heteroscedastic noise in bandits and reinforcement learning. In these works, the cumulative

CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering

arXiv:2607.24236v1 Announce Type: new Abstract: Long-form question answering increasingly relies on retrieved evidence to make LLM outputs verifiable, with inline citations tracing claims to source do

Calibrated Tree-Neural Fusion for Fine-Grained Vegetation Community Classification

arXiv:2607.24160v1 Announce Type: new Abstract: Accurate vegetation-community classification is essential for ecological monitoring, habitat assessment, and evidence-based environmental management in

Calibration-Free 3D Multi-Camera People Tracking for Indoor Environment

arXiv:2607.22731v1 Announce Type: new Abstract: Multi-Camera People Tracking (MCPT) traditionally relies on precise intrinsic and extrinsic camera calibration to project 2D detections into a unified 3

Can an Actor-Critic Optimization Framework Improve Analog Design?

arXiv:2603.24714v2 Announce Type: replace Abstract: Analog design often slows down because even small changes to device sizes or biases require expensive simulation cycles, and high-quality solutions

Capacity-Aware Deep Learning for Generalizable Traffic Volume Estimation Across Links and Cities

arXiv:2607.24056v1 Announce Type: cross Abstract: Network-wide traffic volume estimation typically relies on propagating measurements from fixed sensors, making performance highly dependent on sensor

CAPT: A Multi-task Continuous Autoregressive Transformer enabling Cross-dataset and Cross-species Transfer for Calcium Population Dynamics

arXiv:2607.23258v1 Announce Type: new Abstract: Large-scale calcium imaging has created an opportunity to build foundation-style models for neural population dynamics, but a central question remains u

Cascade Forgery Mining Network for Fingerprint Presentation Attack Detection

arXiv:2607.24090v1 Announce Type: new Abstract: Fingerprint Presentation Attack Detection (PAD) is a critical component of fingerprint identification systems, serving as a protective measure against u

Catalyst Diffusion Transformer: Generative Inverse Design of Heterogeneous Catalysts

arXiv:2607.24272v1 Announce Type: cross Abstract: The vast chemical design space and complex, interdependent design variables make catalyst discovery for targeted properties highly labor- and resource

CausAdv: A Causal-based Framework for Detecting Adversarial Examples

arXiv:2411.00839v4 Announce Type: replace-cross Abstract: Deep learning has led to tremendous success in computer vision, largely due to Convolutional Neural Networks (CNNs). However, CNNs have been s

Characterisation of Density-based FM generation methods in the context of Information Fusion

arXiv:2607.23243v1 Announce Type: new Abstract: Fuzzy Integral (FI) based aggregation provides a powerful mechanism for nuanced aggregation, for example, in ensemble approaches or decision-level fusio

Characterizing Arbitrary Lindbladian Dynamics with a Few Pauli Measurements

arXiv:2607.23044v1 Announce Type: cross Abstract: Quantum devices are open systems whose dynamics interleave coherent evolution with dissipation, and benchmarking, error mitigation, and error correcti

Charging Phase Health Indicators for Battery State-of-Health Estimation: A Systematic Comparison of CC, CV, and Combined Approaches under Cross-Battery Validation

arXiv:2607.23482v1 Announce Type: new Abstract: Accurate State-of-Health estimation is essential for safe battery operation and cost-effective maintenance. Although numerous health indicators have bee

CHiPS: Character Histograms and Positional Signals for Lightweight Authorship Attribution in Romanian Texts

arXiv:2607.22884v1 Announce Type: new Abstract: We propose CHiPS, a lightweight character-level authorship attribution method for Romanian texts. All reported experiments are closed-set: the true auth

Co-Evolving Graph and Text Memory for Training-Free Multi-Hop Question Answering

arXiv:2607.23278v1 Announce Type: new Abstract: Multi-hop question answering requires coordinating relational and textual evidence across reasoning steps, a combination neither a text corpus nor a kno

Codebook Capacity Governs Perceptual Quality Across Resolutions in Hierarchical Discrete Video Compression

arXiv:2607.23366v1 Announce Type: cross Abstract: Learned video codecs based on continuous latent representations typically require resolution-specific retraining or rate-distortion (RD) recalibration

Codifying the Judge: Scalable Evaluation via Program Distillation

arXiv:2607.22561v1 Announce Type: new Abstract: LLM-as-a-judge has become the standard for automated evaluation, but it suffers from high cost, significant latency, and opaque decisions -- limitations

Color Fundus Photography Analysis: Co-evolution of Data, Preprocessing, and Modeling toward Multimodal AI

arXiv:2607.23972v1 Announce Type: new Abstract: Color Fundus Photography (CFP) is a primary non-invasive imaging modality for large-scale screening of ophthalmic and systemic diseases. Existing survey

Comparing Optimization Models for Radiotherapy Scheduling

arXiv:2607.22539v1 Announce Type: cross Abstract: The Radiotherapy Scheduling Problem (RTSP) involves determining an optimal schedule for patients undergoing radiation treatments, a task that has a ma

Continuous surrogates versus threshold Boolean networks for modeling Arabidopsis ISR gene regulation

arXiv:2607.23289v1 Announce Type: cross Abstract: Gene regulatory network modeling often requires balancing predictive accuracy and mechanistic interpretability. In this work, we compare continuous su

Copula Based Fusion of Clinical and Genomic Machine Learning Risk Scores for Breast Cancer Risk Stratification

arXiv:2511.17605v2 Announce Type: replace Abstract: Clinical and gene-expression models predict breast cancer outcomes, but simple linear fusion ignores dependence between their risk scores. Using MET

Covariance Last-Layer Ensembles: Function-Space Diversity for Efficient Uncertainty Quantification

arXiv:2607.23856v1 Announce Type: new Abstract: A Last-Layer Ensemble (LLE), K linear units on one shared frozen feature map, is an efficient single-pass approach to the disagreement-based epistemic u

Creative Integration: A Decidable Criterion of Creativity

arXiv:2606.13977v1 Announce Type: cross Abstract: 'Integrative' solutions are widely praised but rarely defined: we lack an operational way to tell a genuine integration -- one that makes the world ch

Cross-Attention Calibrated Deduplication for Retrieval-Augmented Generation System

arXiv:2607.24332v1 Announce Type: new Abstract: Common chunking strategies in Retrieval-Augmented Generation (RAG) systems often create redundant chunks. These redundant chunks make the vector databas

CuraWeb: Joint Optimization of Quality, Redundancy, and Diversity for Web-Scale Pretraining Data

arXiv:2607.22662v1 Announce Type: new Abstract: Open-web corpora curated via highly selective filters, such as FineWeb-Edu and DCLM, constitute the core of LLM pretraining data and have significantly

Data-Driven Diffusion Processes on Differential Forms via the Projected Ambient Connection Laplacian

arXiv:2607.23192v1 Announce Type: cross Abstract: We develop a data-driven approximation of the projected ambient connection Laplacian acting on differential forms over smooth Riemannian manifolds sam

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data

arXiv:2607.24717v1 Announce Type: cross Abstract: Pretraining data processing is critical to the downstream performance of Large Language Models (LLMs). However, many existing approaches define a fixe

DDVT: Dynamic Dual-level Vision Transformer Fusion Network for Answer Grounding in Visual Question Answering

arXiv:2607.23921v1 Announce Type: new Abstract: Answer grounding in visual question answering aims to locate the region from a given natural language question associated with the visual content of an

DECAF: De-Clustering for Adaptive Representational Unlearning

arXiv:2607.23934v1 Announce Type: new Abstract: Machine unlearning, which aims to remove the influence of specific training data from a trained model, is a key requirement for privacy, accountability,

Decision trees, Frobenius traces, and Weierstrass coefficients of elliptic curves

arXiv:2607.24251v1 Announce Type: cross Abstract: We investigate the extent to which the reduced minimal Weierstrass coefficients of an elliptic curve over Q may be computed from it's Frobenius traces

DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding

arXiv:2607.24554v1 Announce Type: cross Abstract: Advancing multimodal retrieval-augmented generation (RAG) for complex document understanding presents a formidable dual dilemma of accuracy and effici

DecoupleMix: Decoupled Ratio Search and Convex Allocation for Scalable VLM Data Recipes

arXiv:2607.24516v1 Announce Type: cross Abstract: While data curation for Vision Language Models (VLMs) is increasingly active, public practice for constructing pretraining mixtures remains largely he

Denoising 3D images: robustness of persistent homology measures

arXiv:2607.24579v1 Announce Type: cross Abstract: When computing sub/super-level-set persistent homology (PH), the effect of noise may introduce millions of (short-lived) topological generators, prese

Development of a Handheld Actuation Mechanism for a Tendon-driven Robotically Steered Guidewire

arXiv:2607.24629v1 Announce Type: new Abstract: An endovascular intervention begins with a skilled clinician manually navigating a long, slender wire, called a guidewire, to the target location within

researcharxiv-cs-ro

Differencing the Diffusion Trajectory toward Uncertain Components for Time Series Forecasting

arXiv:2607.22599v1 Announce Type: new Abstract: Diffusion models have become a widely used framework for probabilistic time series forecasting, modeling the distribution of future values given an obse

DINOv3-MIL: Per-Kidney Multi-Label Tumour and Cyst Detection from Foundation-Model Patch Tokens on KiTS23

arXiv:2607.22687v1 Announce Type: new Abstract: Foundation vision models trained on natural images transfer to medical tasks without domain pre-training, but volumetric classification requires aggrega