research

Multi-Stage NeRF for Efficient 3D Coronary Artery Reconstruction from Two Narrow-Angle Angiographic Projections

arXiv:2609.15550v1 Announce Type: cross Abstract: X-ray coronary angiography is the clinical gold standard for coronary artery disease during real-time cardiac interventions, but provides only 2D proj

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Multi-View Structure-from-Motion Enables Oriented Projective Shape Analysis in Three Dimensions

DGX agent

arXiv:2609.13263v1 Announce Type: new Abstract: Projective shape analysis provides a geometric framework for studying landmark configurations in digital images acquired by pinhole cameras. In the clas

researcharxiv-cs-cv

15 Sept 2026

Multimodal deep learning from spectra for small-molecule structure identification: enhancing robustness with mixed-condition training

arXiv:2609.14360v1 Announce Type: new Abstract: In practical molecular characterization, small-molecule structure identification benefits from complementary spectroscopic evidence, but missing, degrad

MuPlon: Multi-Path Causal Optimization for Claim Verification through Controlling Confounding

arXiv:2509.25715v2 Announce Type: replace-cross Abstract: As a critical task in data quality control, claim verification aims to curb the spread of misinformation by assessing the truthfulness of clai

researcharxiv-cs-cl

NavPatch: Evidence-Guided Object-Level Costmap Correction with Vision-Language Models

arXiv:2609.14543v1 Announce Type: new Abstract: Mobile robots typically rely on geometric maps for obstacle avoidance and path planning, but the resulting obstacle representation does not always match

researcharxiv-cs-ro

Neural Modal Decomposition: Architectural Priors from Observables

arXiv:2609.14402v1 Announce Type: cross Abstract: Many engineering building blocks behave as multi-port linear time-invariant systems. RF cavities, photonic devices, and superconducting quantum chips,

Neural Network Operator-Based Fractal Approximation: Smoothness Preservation and Convergence Analysis

arXiv:2505.06229v2 Announce Type: replace Abstract: This paper introduces the construction of fractal interpolation functions (FIFs), whose graphs are the attractors of an iterated function system (IF

Neural-Network Solutions to Real-Space Charge Density and Generalization

arXiv:2609.14906v1 Announce Type: cross Abstract: The Hohenberg-Kohn theorem establishes that, in principle, the ground state (GS) charge density contains all GS information of a many-electron system,

NeuroActiSep: Detecting Factual Hallucinations from Feed-Forward Neurons in a Single Pass

arXiv:2609.14448v1 Announce Type: cross Abstract: Hallucination in large language models reduces their reliability and slows adoption. Various white-box studies have used internal representations to d

NeuroFlex: Lossless Element-Level ANN-SNN Co-Execution for Efficient Sparse Inference

arXiv:2609.14092v1 Announce Type: cross Abstract: Sparse DNN accelerators specialize in ANN or SNN execution, leaving energy or latency on the table when workload characteristics vary within a layer.

Neuron Activation-based Computation of Logical Explanations for Deep Neural Networks

arXiv:2609.14099v1 Announce Type: cross Abstract: Formal explainability of classifying neural networks (NNs) is an active area of research, providing explanations with provable guarantees of the class

Newton Deep Unfolding for Compressed Sensing

arXiv:2609.14391v1 Announce Type: new Abstract: Compressed sensing (CS) reconstructs images from highly limited measurements, but existing deep unfolding methods are typically driven by first-order op

Not All Duplicates Are Coordination: Generic vs. Non-Generic Duplicate Campaigns in Information Operations

arXiv:2609.13671v1 Announce Type: cross Abstract: Duplicate content is widely used to study coordinated behavior in social media information operations (IOs), but not all repetition provides equally m

Not all Negation Cues are Equal: Affixal Negations Yield Better Negation Understanding

arXiv:2609.13685v1 Announce Type: cross Abstract: Negation remains a longstanding challenge for both language models (LMs) and large language models (LLMs). Prior work mainly focuses on a small set of

Novel Ex-vivo Calf Brain Model with Integrated Sub-Skull Force Sensors to Access Simulated Neurosurgical Procedures

arXiv:2609.14198v1 Announce Type: new Abstract: Surgical tissue manipulation demands precision; however, tool-tissue manipulation force magnitudes under realistic conditions are rarely quantified. To

researcharxiv-cs-ro

OCT-FedSIR: Toward Trustworthy Federated Ophthalmic Learning under Annotation Noise

arXiv:2609.14734v1 Announce Type: cross Abstract: Federated learning enables collaborative model development without centralizing patient data, but annotation reliability at participating institutions

Omni-Streaming Thinking

arXiv:2609.15128v1 Announce Type: new Abstract: Streaming omni-modal models must decide what and when to answer from the video chunks and synchronized audio observed so far. Visual cues often support

On the Equivalence of Stochastic Control and Path Space Formulations for Schrodinger Bridges over Compact Connected Lie Groups

arXiv:2609.13758v1 Announce Type: cross Abstract: We establish the equivalence between the stochastic optimal control and path space formulations of the Schrodinger bridge problem (SBP) for the kinema

On the Potential of Multi-Task Learning in Predictive Process Monitoring

arXiv:2609.13477v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) forecasts how ongoing organizational processes unfold, enabling information systems to move beyond execution support

On the role of the tokenizer in ECG transformer models

arXiv:2609.15433v1 Announce Type: cross Abstract: Tokenization determines both the physiological content presented to an ECG Transformer and the sequence over which attention operates. We compare eigh

One Spectrum, Two Resources: Data-Memory Scaling in Autoregressive Prediction

arXiv:2609.13500v1 Announce Type: cross Abstract: How much learned memory is needed to benefit from more data? We show that the two resources are governed by one predictive-energy spectrum in a positi

Online local learning for generative thermodynamic computing

arXiv:2609.15439v1 Announce Type: cross Abstract: Generative thermodynamic computers turn thermal noise into structured data through Langevin dynamics. We train these systems with a local update at ea

Option-Aware Retrieval and Task-Specific VLM Adaptation for Medical VQA

arXiv:2609.15530v1 Announce Type: new Abstract: We describe our submission to the MedReason 2026 challenge, covering multiple-choice (MCQ) and open-ended (OE) medical visual question answering (VQA) u

P-POSEMEM: Projective Semantic Memory for Consistent Language Grounding under Pose-Graph Rewrites

arXiv:2609.15475v1 Announce Type: new Abstract: A robot following language instructions needs its semantic memory to keep naming the same physical object while the SLAM pose graph underneath is optimi

researcharxiv-cs-ro

Partition Scores Are Not System Scores: Deployment-Fidelity Gaps in Decomposed Algorithm Selection

arXiv:2609.13785v1 Announce Type: new Abstract: Oracle-style quantities, including virtual best solvers, selected-portfolio VBS, virtual-best encodings, and best-in-family summaries, are widely report

Pathwise Individual Rationality in Federated Learning: A Mechanism-Architecture Co-Design

arXiv:2609.14591v1 Announce Type: new Abstract: Participation in federated learning (FL) comes at a cost. Clients trade off privacy, communication, and compute costs for potentially greater gains in m

PC^2-AD: Point Cloud Upsampling to Safeguard 3D Anomaly Detection with Resolution-constrained Edge Devices

arXiv:2609.14722v1 Announce Type: new Abstract: Low-cost and low-resolution sensors used in edge deployments can produce test point clouds that are substantially sparser than the normal training data.

PeerPen: AI-Assisted Writing for Online Mental Health Peer Support

arXiv:2609.14886v1 Announce Type: cross Abstract: Online mental health communities thrive on peer support, yet those who volunteer to help often lack formal training and may struggle to articulate sup

Perceive, Refine, Reason: A Calibrated Pipeline for Measuring Indicators in Strategic Visual Communication on Social Media

arXiv:2609.14699v1 Announce Type: new Abstract: Visual content shapes audience perception and opinion on social media, and computational social science increasingly relies on automated tools to analyz

Perceptual Reality Transformer: What Must an Illustration Preserve?

arXiv:2508.09852v2 Announce Type: replace-cross Abstract: How can models help people communicate unusual perceptual experiences without changing what they mean? A recognizable image is only part of th

Physics Informed Neural Network model for the dynamical study of Abdominal Aortic Aneurysm

arXiv:2609.15104v1 Announce Type: cross Abstract: We present the development and application of a three-dimensional Physics-Informed Neural Network (PINN) framework for the investigation of haemodynam

Pixel-wise Planarity for High-Precision Monocular Plane Segmentation

arXiv:2609.13246v1 Announce Type: new Abstract: Plane segmentation from a single RGB image remains challenging due to imprecise region grouping and geometrically inconsistent supervision, often leadin

Planning as Dynamics Relaxation: Hippocampal Recurrent Network Realizes Optimal Goal-Directed Navigation

arXiv:2609.13219v1 Announce Type: cross Abstract: Neural correlates of spatial cognitive map are well documented, yet exactly how neural circuits perform spatial navigation in complex environments - e

Planning in the Backbone: DiffAdapterVLA for Native Continuous Trajectory Generation with Driving VLMs

arXiv:2609.15322v1 Announce Type: cross Abstract: Pretrained driving vision-language models (VLMs) integrate visual, route, language, and driving context into rich driving priors, yet their representa

Potential of Artificial Intelligence Algorithms for Identification of Relevant Diagnostic and Prognostic Biomarkers of Early-Stage Liver Cancer

arXiv:2609.15638v1 Announce Type: new Abstract: This study explores the use of deep learning and explainable artificial intelligence to diagnose hepatocellular carcinoma (HCC) and define effective bio

Pre-training with Graph Transformers

arXiv:2609.13844v1 Announce Type: new Abstract: This article investigates pre-training strategies for graph transformers in the biochemistry domain. By conducting comprehensive experiments, the study

Predictive Likelihood Ratios for Language Model Watermark Detection

arXiv:2609.15657v1 Announce Type: cross Abstract: Keyed watermark detection tests dependence between observed tokens and pseudorandom variables reconstructed from a secret key. Building on the pivotal

Prescreening Point Defects in Semiconductors With Machine Learning

arXiv:2609.14846v1 Announce Type: cross Abstract: High-throughput calculations using density-functional theory (DFT) are commonly used to explore point defects for applications in power electronics an

Privacy-Aligned Personalized Federated Learning with Compact Adaptation and Variable-Length Gaussian Communication

arXiv:2609.15950v1 Announce Type: new Abstract: Record-level differential privacy exposes a structural misalignment in personalized federated learning when client-specific variation is low-dimensional

Privacy-Preserving Deep Joint Source-Channel Coding with In-Loop Concept Erasure

arXiv:2609.13393v1 Announce Type: cross Abstract: Deep joint source-channel coding (DeepJSCC) transmits learned semantic features efficiently but can leak sensitive attributes such as gender, race, or

Proving olympiad geometry theorems on a superconducting quantum processor

arXiv:2609.14533v1 Announce Type: cross Abstract: Automated theorem proving seeks to use computational systems to prove or disprove mathematical and logical statements [1, 2]. It underpins a wide rang

Proximal-Only Transmission Matrix Recovery of an Arbitrarily Deformed Graded-Index Multimode Fiber

arXiv:2609.14869v1 Announce Type: cross Abstract: The multimode fiber is among the thinnest imaging conduits available, carrying hundreds to thousands of spatial modes through a cross-section comparab

Pruning as Regularization: Sensitivity-Aware One-Shot Pruning in ASR

arXiv:2511.08092v2 Announce Type: replace-cross Abstract: We challenge the conventional view of neural network pruning as solely a compression technique, demonstrating that one-shot magnitude pruning

researcharxiv-cs-cl

Psychosis involves a deficit of information compression in connected speech

arXiv:2609.15522v1 Announce Type: new Abstract: Large language models (LLMs) with human-like performance on linguistic tasks have transformed the study of language in neurodiverse conditions. LLMs pro

researcharxiv-cs-cl

Quenched Ensemble Sampling

arXiv:2609.15894v1 Announce Type: cross Abstract: Some of the sharpest challenges in sampling from the energy functions of physical systems arise at phase transitions, where the density of states chan

Random matrix theory of sparse neuronal networks with heterogeneous timescales

arXiv:2512.12767v2 Announce Type: replace-cross Abstract: Training recurrent neuronal networks consisting of excitatory (E) and inhibitory (I) units with additive noise for working memory computation

Rank-Consistent Set Reasoning for Co-Salient Object Detection

arXiv:2609.13706v1 Announce Type: new Abstract: Co-salient object detection (Co-SOD) requires a model to find foreground regions that are salient in individual images and supported by the image group.

Real-time Learning and Evolution in Robotic Art Installations

arXiv:2609.13352v1 Announce Type: cross Abstract: We present three robotic art installations which explore the aesthetics of adaptive behavior. Through embodied machine leaning and digital evolution,