Search: “research”

LaSeD: Label-Semantic Self-Distillation for Visual-Only Surgical Phase Recognition

arXiv:2609.18971v1 Announce Type: new Abstract: Surgical phase recognition maps each video frame to a clinically meaningful workflow phase, supporting context-aware assistance, documentation, and post

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Learning A Unified Template for Gait Recognition

DGX agent

arXiv:2609.18490v1 Announce Type: new Abstract: 'What I cannot create, I do not understand.'Human wisdom reveals that creation is one of the highest forms of learning. For example, Diffusion Models ha

researcharxiv-cs-cv

17 Sept 2026

Learning Lyapunov Operators for Nonlinear Systems

arXiv:2609.18894v1 Announce Type: cross Abstract: Constructing Lyapunov functions for nonlinear dynamical systems is a central problem in stability analysis, yet remains challenging. Lyapunov function

Learning Nuclear Structure with AI: Radii and Collectivity

arXiv:2609.17838v1 Announce Type: cross Abstract: Low-energy nuclear structure is encoded in a broad body of experimental information across the chart of nuclides. Learning how this information is org

Leveraging Complementary Embeddings for Replay Selection in Continual Learning with Small Buffers

arXiv:2604.08336v2 Announce Type: replace Abstract: Catastrophic forgetting remains a key challenge in Continual Learning (CL). In replay-based CL with severe memory constraints, performance criticall

Limits of Transfer Learning

arXiv:2006.12694v2 Announce Type: replace-cross Abstract: Transfer learning involves taking information and insight from one problem domain and applying it to a new problem domain. Although widely use

Lost in Perception: Isolating Perceptual and Reasoning Failures in Multimodal Physics and Geometry Reasoning

arXiv:2609.18991v1 Announce Type: new Abstract: Multimodal LLMs report strong performance on scientific reasoning benchmarks, yet most treat perception and reasoning as a single measurable process. We

LSR-Net: Learning the Forward Evolution Operator for Nonlinear Fluid Dynamics

arXiv:2609.19039v1 Announce Type: cross Abstract: We introduce the Long-Short-Range Neural Network (LSR-Net), a novel neural operator architecture designed for data-driven forward evolution modeling,

LUMO: Designing Luminous Contact Morphology for Repeatable Whole-Finger Contact Observation

arXiv:2609.18165v1 Announce Type: new Abstract: A low-impedance robot finger reports through joint torque how strongly it is loaded, but the same torque can arise from a small force near the fingertip

researcharxiv-cs-ro

M^3P-R1: Reinforcement Learning for Large Language Model Guided Multi-Modal Motion Planning via MIP Code Generation

arXiv:2609.18669v1 Announce Type: new Abstract: Multi-Modal Motion Planning (M^3P) requires joint reasoning over continuous motions and discrete mode transitions, making it difficult to solve efficien

researcharxiv-cs-ro

Made in Hungary: Comments on the performance of generative language models

arXiv:2609.18284v1 Announce Type: new Abstract: In recent years, three initiatives have emerged to develop generative language models in Hungary. The motivation behind them is the same. For Hungarian,

Mask 2D-3D: Adaptive Dual-Masked Autoencoder Network for Image-to-Point Cloud Registration

arXiv:2609.18088v1 Announce Type: cross Abstract: Detection-free methods for image-to-point cloud registration are prone to erroneous correspondences caused by domain and modality discrepancies, limit

Matching Multi-Loop Complexities with a Single Loop: Optimal Optimization Stationarity and Best-Known Game Stationarity in Nonconvex--Concave Minimax Optimization

arXiv:2609.17973v1 Announce Type: cross Abstract: We introduce a new single-loop algorithmic framework for smooth nonconvex--concave minimax optimization. The resulting projected damped extragradient

Maximum Strong Independent Sets in Hypergraphs: Reductions, Bounds, and Greedy Certificates

arXiv:2609.17951v1 Announce Type: new Abstract: We study the maximum strong independent set problem in a finite hypergraph: find the largest vertex set that intersects every hyperedge in at most one v

Memory Has Geometry: Non-Uniform Geometric Memory for Long-Horizon Personalized AI

arXiv:2609.17969v1 Announce Type: new Abstract: Long-term memory is becoming a core substrate for personalized AI, yet most systems still represent personalization as discrete records in a largely sta

MI-DETR: A Strong Baseline for Moving Infrared Small Target Detection with Motion Integration

arXiv:2603.05071v2 Announce Type: replace Abstract: Detecting moving infrared small targets is challenging because tiny, low-contrast targets occupy few pixels and are easily obscured by dynamic backg

MINT: Multimodal Imaging-to-Speech Knowledge Transfer for Early Alzheimer's Screening

arXiv:2602.23994v2 Announce Type: replace-cross Abstract: Alzheimer's disease is a progressive neurodegenerative disorder in which mild cognitive impairment (MCI) precedes dementia. Structural MRI pro

Modeling the Developmental Shift in Telicity Acquisition

arXiv:2609.17996v1 Announce Type: new Abstract: Acquiring telicity, which is the distinction between bounded (e.g., ate an apple) and unbounded (e.g., ate apples) events, requires first language (L1)

Multi-Hop Knowledge Composition is Bound by Pretraining Exposure

arXiv:2606.09338v2 Announce Type: replace Abstract: Large Language Models fail at implicit multi-hop reasoning: a model answers 'When was X born?' and 'Who is Y's closest friend?' correctly but fails

Myovox: Reading Speech from the Muscles of the Face

arXiv:2609.17548v1 Announce Type: new Abstract: Myovox, from myo (muscle) and vox (voice), decodes open-vocabulary English text from 31-channel surface electromyography (sEMG) recorded from the muscle

NeuroECG: ECGFounder-Based Deep ECG Representation for EEG-Free Neurological Prognostication After Cardiac Arrest

arXiv:2609.18891v1 Announce Type: cross Abstract: Neurological prognostication after cardiac arrest commonly relies on electroencephalography (EEG). However, EEG demands high clinical resources. Bedsi

Not All Patches Are Equally Forgettable: Spatially Localized Domain Unlearning in Vision-Language Models

arXiv:2609.17790v1 Announce Type: new Abstract: Pre-trained vision-language models (VLMs) exhibit strong cross-domain recognition performance even without additional training. However, this robustness

Objective vs. Search: Decomposing What Makes a Good Tokeniser

arXiv:2609.19145v1 Announce Type: cross Abstract: Two dominant tokenisation algorithms are used by modern language models: byte-pair encoding (BPE) and UnigramLM. These differ along two orthogonal axe

On Dominant Manifolds in Reservoir Computing Networks

arXiv:2604.05967v2 Announce Type: replace Abstract: Understanding how training shapes the geometry of recurrent network dynamics is a central problem in time-series modeling. We study the emergence of

On-the-Fly Homographies Calibration for Multi-Camera Tracking

arXiv:2609.18582v1 Announce Type: cross Abstract: Precise multi-camera tracking traditionally relies on rigorous 3D site calibration, yet this requirement is often operationally impossible in large-sc

Online Multi-Camera 3D Tracking via ID Prediction over Recurrent Sparse Queries

arXiv:2609.18363v1 Announce Type: new Abstract: Online multi camera 3D tracking must maintain scene global identities across synchronized views, yet query-based trackers carry these identities only im

Online Multimodal Workload Assessment in Contact-Rich Physical Human-Robot Interaction

arXiv:2609.18031v1 Announce Type: new Abstract: Contact-rich physical human--robot interaction (pHRI) imposes time-varying demands associated with physical interaction, motor regulation, and physiolog

researcharxiv-cs-ro

Peak-Aware Short-Term Load Forecasting Across Distribution Grid Aggregation Levels

arXiv:2609.18588v1 Announce Type: new Abstract: For distribution system operators, short-term load forecasting (STLF) supports congestion management, voltage control, and asset protection. Most existi

Physics-based prediction, uncertainty quantification and decision-making for IN718 crystallographic texture intensity across LPBF defocus regimes

arXiv:2609.18863v1 Announce Type: new Abstract: Reliable prediction of crystallographic texture in laser powder bed fusion is critical for linking process conditions with anisotropic response and for

Preservation of Log-Concavity and Convergence of Wasserstein-Fisher-Rao Gradient Flows

arXiv:2609.18118v1 Announce Type: cross Abstract: We study the convergence of Wasserstein-Fisher-Rao (WFR) gradient flows for sampling from probability distributions known up to a normalisation consta

Preventing Model Collapse: A Fisher-Rao Perspective on the Dynamics of Training with Synthetic Data

arXiv:2609.18878v1 Announce Type: new Abstract: Large Language Models (LLMs) are now routinely trained using synthetic data, since high-quality human data has been exhausted by the ever increasing nee

Principled Koopman Representations with Kalman Inference for Efficient Time-Series Prediction

arXiv:2609.17815v1 Announce Type: cross Abstract: The Koopman operator has been widely used for time-series prediction in dynamical systems. However, prior work that learns latent ``Koopman spaces'' u

Prior-Free Competitive Ratios for Improving Bandits: Scale, Curvature and Horizon Are Free, but Not Jointly Under Noise

arXiv:2609.17595v1 Announce Type: new Abstract: In the improving multi-armed bandits problem, each of k arms has an unknown nondecreasing, discretely concave reward curve f_i, and pulling arm i for th

Probabilistic Linear Explanations

arXiv:2609.19077v1 Announce Type: cross Abstract: Formal explainability provides mathematically grounded justifications for individual predictions. However, abductive explanations often exceed human c

ProofVerifier: A Scalable, Diversity-Driven Framework for Natural-Language Proof Verification

arXiv:2602.02377v3 Announce Type: replace Abstract: While large language models (LLMs) have achieved strong performance on mathematical problems with verifiable answers, many advanced problems are pro

Provable Guarantees and Efficient Learning of Structural Equation Models with Latent Confounders

arXiv:2609.18535v1 Announce Type: new Abstract: Causal discovery aims to recover causal relationships from observed data. In various fields, exploring causal relationships among variables remains an i

Provable Guarantees for Spectral Structured Prediction

arXiv:2609.18527v1 Announce Type: new Abstract: Structured prediction is the simultaneous prediction of multiple labels, and is widely used in various fields, such as natural language processing and c

Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization

arXiv:2603.27526v2 Announce Type: replace Abstract: Protein fitness optimization is a discrete search problem, and the representation used for prediction also determines the neighborhood graph travers

QiT: Quantum-Inspired Transformer for Visual Recognition Task

arXiv:2609.17789v1 Announce Type: cross Abstract: Quantum machine learning offers a compelling representational perspective: angle-encoded states inhabit Hilbert spaces in which periodic similarities

Quanta: A Self-Contained Python Library for Hybrid Retrieval over Quantised Embeddings, Lexical Indexes, and Knowledge Graphs

arXiv:2609.18248v1 Announce Type: cross Abstract: An advanced retrieval-augmented generation pipeline is typically assembled from three or four independently operated systems: an approximate nearest-n

Rank and computation of the pathlifting Jacobian of a DAG ReLU network

arXiv:2609.18682v1 Announce Type: cross Abstract: This paper provides a self-contained proof of the rank of the pathlifting Jacobian of a DAG ReLU network by performing an induction on the network's n

Rapid Loss of the Sierra Nevada's Largest Trees Driven by Fire

arXiv:2609.17925v1 Announce Type: new Abstract: Large trees disproportionately contribute to biomass storage, habitat structure, and ecosystem functioning. However, their distribution and health dynam

Reaching Every Position Without Searching: Rotating Sparse Wiring on the Hypercube as a Substitute for Attention

arXiv:2609.18145v1 Announce Type: new Abstract: Attention pays, at every layer and for every input, the cost of searching for whom to connect. We ask how far one can get with wiring that is fixed, spa

ReDIL-GNN: Resynthesis Domain Incremental Learning for Circuit Graph Neural Networks

arXiv:2609.18595v1 Announce Type: new Abstract: Logic resynthesis preserves circuit functionality while changing gate vocabulary, topology, and structural statistics, creating domain shift for circuit

Regional Explanations via Causal Sufficiency and Necessity

arXiv:2609.18049v1 Announce Type: new Abstract: Model explainability is essential for understanding and trusting machine learning models. Existing explainable AI methods often explain predictions thro

Regularized Least Squares Training of Quadratic Neural Networks with Applications to System Identification

arXiv:2609.17654v1 Announce Type: new Abstract: This paper proposes a least squares approach for the training of quadratic neural networks with regularization. The proposed methodology yields a lower

Relation Before Entity: Deferred Commitment in Language Model Factual Recall

arXiv:2609.17537v1 Announce Type: new Abstract: We ask whether relation-type information (e.g., capital-of) and entity-specific information (e.g., France to Paris) become causally active at the final-

Relationally Guided Use Case Modeling with LLMs

arXiv:2609.18291v1 Announce Type: cross Abstract: Use case flows are important elements of use case modeling because they support downstream software engineering activities, including requirements ana