Search: “research”

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

arXiv:2412.19990v3 Announce Type: replace-cross Abstract: Hepatic vessels in computed tomography scans often suffer from image fragmentation and noise interference, making it difficult to maintain ves

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Research

Semi-Tensor Product-Based Multi-Term Randomized T-SVD and Its Visual Applications

DGX agent

arXiv:2609.11168v1 Announce Type: new Abstract: Tensor singular value decomposition (T-SVD), which is built upon the tensor-tensor product (t-product), has emerged as a powerful tool for processing hi

researcharxiv-cs-lg

11 Sept 2026

Semidefinite Programming for Quantum Channel Learning

arXiv:2601.12502v2 Announce Type: replace Abstract: The problem of reconstructing a quantum channel from a sample of classical data is considered. When the total fidelity can be represented as a ratio

Shifting Relational Paradigms for Affective Computing: Affective Resonance, Vitality Affects, and Vocal Interaction Fields

arXiv:2609.09864v1 Announce Type: new Abstract: Affective computing has largely followed an individual-state paradigm, extracting discrete emotion labels or arousal/valence from isolated speakers. We

Single-Stream Multi-Feature Fusion with Temporal Robustness for Gait Emotion Recognition

arXiv:2609.11680v1 Announce Type: new Abstract: 3D skeleton-based gait emotion recognition faces high annotation costs, data scarcity, and poor generalization on heterogeneous data. This paper propose

Sparsity Regularized and Robust Mean Variance Portfolio Selection Under Ellipsoidal Uncertainty

arXiv:2609.11749v1 Announce Type: cross Abstract: We investigate mean-variance portfolio selection with an ell_0-penalty to promote sparsity in asset allocations. Uncertainty in the mean return vector

SpecGuard: Inference-Time Backdoor Detection For Free

arXiv:2609.11799v1 Announce Type: cross Abstract: Large language models are often fine-tuned, shared, or downloaded from third parties, so a deployed model may carry a hidden backdoor that behaves nor

Strategic Type Spaces

arXiv:2606.08297v2 Announce Type: replace-cross Abstract: We provide a strategic foundation for information: in any given game with incomplete information we define strategic quotients as information

Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters

arXiv:2501.12299v3 Announce Type: replace-cross Abstract: Gaussian Mixture Models (GMMs) range among the most frequently used models in machine learning. However, training large, general GMMs becomes

SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations

arXiv:2609.11414v1 Announce Type: new Abstract: Large language models exhibit complementary strengths, motivating routing methods that dispatch each query to the most suitable model. Although existing

TailProp: content-adaptive light- and heavy-tailed propagation for vision

arXiv:2609.11081v1 Announce Type: new Abstract: Science-inspired vision models show that explicit propagation dynamics can provide structured and interpretable alternatives to conventional token mixin

Talking to Itself While Coding: What Makes Comments Help Code Generation?

arXiv:2609.09242v1 Announce Type: cross Abstract: Large Language Models (LLMs) often generate natural-language comments while writing code, and these comments become part of the context used to genera

Temporal and Multimodal Deep Learning for Cyberattack Detection in LEO Satellite Systems

arXiv:2609.10746v1 Announce Type: cross Abstract: The growing reliance on Low-Earth Orbit (LEO) satellite communication systems has increased the need for intelligent methods capable of detecting cybe

Test time training enhances in-context learning of nonlinear functions

arXiv:2509.25741v3 Announce Type: replace-cross Abstract: Test-time training (TTT) enhances model performance by explicitly updating designated parameters prior to each prediction to adapt to the test

The observational partial order of causal structures with latent variables

arXiv:2502.07891v3 Announce Type: replace-cross Abstract: For two causal structures with the same set of visible variables, one is said to observationally dominate the other if the set of distribution

The Semantic Elevation Operator and the Closure of the Undecidable Class under Preservation

arXiv:2609.11326v1 Announce Type: cross Abstract: The undecidability of a program's static semantic properties is governed by Rice's theorem. Self-modifying systems, however, require analysing not whe

The Vibe Shift in Software Engineering: Evaluating AI-Led Conversational Programming for Performance, Cognition, and Responsible Adoption

arXiv:2609.09560v1 Announce Type: cross Abstract: This study evaluates Vibe Coding, an emerging AI-led conversational programming paradigm that enables developers to generate software through natural-

Thompson Sampling for Non-Monotone Convex Ridge Bandits: Monotonicity Is Not Needed for Polynomial Regret

arXiv:2609.10981v1 Announce Type: new Abstract: Bakhtiari, Lattimore and Szepesvari (COLT 2025) proved that Thompson sampling (TS) has Bayesian regret ilde O(d^{5/2}sqrt n) for bandit convex optimisat

Time-Varying Graph Learning with Constraints on Graph Temporal Variation

arXiv:2001.03346v4 Announce Type: replace-cross Abstract: We propose a novel framework for learning time-varying graphs from spatiotemporal measurements. Given an appropriate prior on the temporal beh

Topological Necessities: Mechanism-Invariant Strategic Subgoals for Cross-Embodiment Goal-Conditioned Control

arXiv:2609.11014v1 Announce Type: new Abstract: Long-horizon goal-conditioned reinforcement learning delegates control to a high-level module that proposes subgoals, but existing subgoals are implicit

Toward Interpretable Multimodal Fusion: Heat Conduction Modeling for Hyperspectral and LiDAR Joint Classification

arXiv:2609.11040v1 Announce Type: new Abstract: The fusion of hyperspectral (HS) and Light Detection and Ranging (LiDAR) data plays a crucial role in enhancing land-cover classification by jointly exp

Tri-DehazeGS: Scene--Medium Decoupled Gaussian Splatting with Transmittance-Aware Optimization

arXiv:2609.11223v1 Announce Type: new Abstract: Recovering clean 3D scenes from hazy multi-view images is challenging because haze attenuates scene radiance and introduces atmospheric scattering. Rece

UBone3D: Physics-Rectified Conditional Flow Matching for Anatomical 3D Shape Completion from Ultrasound

arXiv:2609.11506v1 Announce Type: new Abstract: Three-dimensional ultrasound (US) is a safe, radiation-free complementary modality to CT and X-rays for longitudinal monitoring, yet its segmentation-de

UniMPA: A Unified Memory-Prediction-Action Model via Action-Grounded Transition Modeling

arXiv:2609.11875v1 Announce Type: new Abstract: Recent advances in Vision-Language-Action (VLA) models have improved robotic manipulation, yet observation-to-action learning remains limited by a funda

researcharxiv-cs-ro

Using Semantic Uncertainty to Estimate Transition Relevance in Turn-taking

arXiv:2609.10934v1 Announce Type: new Abstract: Turn-taking is a fundamental mechanism that governs when interlocutors speak and listen. Although Spoken Dialogue Systems (SDS) exploit a range of lingu

Vidu S2: Real-Time Interactive, Editable, and Spatial Video Generation

arXiv:2609.11638v1 Announce Type: new Abstract: We present Vidu S2, which comprises Vidu S2-Avatar, a real-time interactive digital-character model, and Vidu S2-Editing, a real-time video editing mode

What Language is This? Ask Your Tokenizer

arXiv:2602.17655v3 Announce Type: replace Abstract: Language Identification (LID) is an important component of many multilingual natural language processing pipelines, where it facilitates corpus cura

When Information is Worth the Risk: Behavioral Valuation for Hazardous Robotic Exploration

arXiv:2609.10726v1 Announce Type: new Abstract: Hazardous robotic exploration requires robots to map spatial risks, such as unsafe terrain, radiation, fire, mines, or structural damage, while operatin

researcharxiv-cs-ro

Why Does Post-Training Quantization Work?

arXiv:2609.11716v1 Announce Type: cross Abstract: Post-training quantization compresses large language models (LLMs) by storing their weights at reduced precision, and each quantized weight introduces

Zero-shot rib design: merging training-free generative prior with topology optimization

arXiv:2609.10643v1 Announce Type: new Abstract: Natural load-bearing patterns such as leaf venation, trabecular bone, and spider webs achieve high stiffness per unit mass, yet classical topology optim

ZipCodec: Ultra-Low-Frame-Rate Streaming Speech Coding

arXiv:2609.11642v1 Announce Type: cross Abstract: Neural audio codecs are a fundamental component of modern speech generation systems. While recent codecs achieve increasingly low bitrates, reducing f

A Block Tensor Train Burer-Monteiro Framework for Low-Rank Quantum State Tomography

arXiv:2609.09457v1 Announce Type: cross Abstract: Quantum state tomography is a fundamental technique for estimating the state of a quantum system from measured data and plays a crucial role in evalua

A convolutional autoencoder and neural ODE surrogate modeling framework applied to transient counterflow flames

arXiv:2603.15038v2 Announce Type: replace-cross Abstract: A novel convolutional autoencoder and neural ODE (CAE-NODE) framework is proposed for a reduced-order model (ROM) applied to transient 2D coun

Model Releases

A Decade of Bayesian Optimization for Controller Tuning and Robot Learning: Tutorial, Review, and Future Prospects

model-releasesarxiv-cs-ro

arXiv:2609.09403v1 Announce Type: new Abstract: In the past decade, Bayesian optimization (BO) has emerged as a powerful and adaptable framework for automatic controller tuning and robot learning. Thi

A Dominant Diffuse Phase in the Sparse Autoencoder Phase Diagram

arXiv:2609.10299v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are increasingly used to recover interpretable features from neural-network activations, yet systematic feature co-occurrence

A Hierarchical Consistency Framework for Auditing Retrieval-Augmented Generation Systems

arXiv:2609.07075v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is commonly evaluated by whether the final answer is correct. That test is insufficient: an answer can match its re

A Jump-Diffusion Framework for Irregular Time Series Generation

arXiv:2505.23215v2 Announce Type: replace-cross Abstract: We propose a framework for generative modeling of continuous-time processes from irregularly and asynchronously recorded data. It is based on

A person with mid single digit years of industry experience and months at one company and negligible external footprint quits that job volun…

A person with mid single digit years of industry experience and months at one company and negligible external footprint quits that job voluntarily and ends up on a press tour that would be the envy of

researchyann-lecun--x

A positive resolution of the gap-entropy conjecture

arXiv:2609.10529v1 Announce Type: new Abstract: We prove the gap-entropy conjecture for fixed-confidence best-arm identification with independent unit-variance Gaussian arms, means in [0,1], and a uni

A Sharp Barrier for Consistent Submodular Maximization: Any Improvement over 2-sqrt{2} Entails Exponential Queries or Linear Recourse

arXiv:2609.09986v1 Announce Type: cross Abstract: Consistent submodular maximization studies the tradeoff between solution quality and stability when elements arrive over time. For a monotone submodul

A solution to the Erdos Problem #1040

arXiv:2609.06050v1 Announce Type: cross Abstract: For a compact set KsubsetC, let artheta(K) be the infimum of the planar areas of the unit lemniscates of all monic polynomials with zeros in K, allowi

A Subsampled Davis-Kahan Bound for Large-Scale Eigenspace Estimation

arXiv:2609.09211v1 Announce Type: cross Abstract: The Davis-Kahan theorem is a fundamental tool in spectral analysis, providing quantitative control over the distance between the eigenspaces of a symm

A TTP by TTP Approach: Precise Malware Detection via Malicious TTP Recognition

arXiv:2609.06579v1 Announce Type: cross Abstract: Machine learning methods, and especially neural networks, are now routinely used for malware detection in network traffic. Though very effective, syst

AAS-RAIL: Improving Information Extraction for Asset Administration Shells through Retrieval-Augmented In-Context Learning

arXiv:2609.07334v1 Announce Type: new Abstract: The Asset Administration Shell (AAS) is a cornerstone of Industry 4.0 and the Digital Product Passport, providing standardized digital representations o

AccelMPC: High-Rate, Low-Power FPGA-Accelerated Model Predictive Control for Tiny Drones

arXiv:2609.09380v1 Announce Type: new Abstract: Unlocking the potential of tiny aerial robots requires order of magnitude improvements in the performance of embedded edge control. In particular, altho

researcharxiv-cs-ro

Accountable and uncertainty-aware evaluation of sensor-based AI under distribution shift: devices, subjects, and nearly three years underground

arXiv:2609.09257v1 Announce Type: new Abstract: Sensor-based AI systems are rarely operated under the conditions under which they were trained: devices, personnel and recording epochs change, and each

Adaptive Distributed Physical-Layer Authentication and Attack Detection in 6G Non-Terrestrial Networks via Causal Meta-Learning

arXiv:2609.09511v1 Announce Type: cross Abstract: Physical-layer authentication (PLA) in non-terrestrial networks (NTNs) is challenged by severe Doppler shifts, long delays, and fast channel variation

AI for AI: Optimizing Additional Infrastructure Build-out to Power Artificial Intelligence Data Centers

arXiv:2609.08166v1 Announce Type: cross Abstract: The twenty-first century's transformative technology, artificial intelligence, is increasingly constrained by the twentieth century's transformative t