Search: “research”

LWCal: Loss-Weighted Calibration for Tabular Classifiers with Noisy Calibration Labels

arXiv:2609.26839v1 Announce Type: cross Abstract: Post-hoc probability calibration is usually evaluated under an optimistic assumption: the held-out calibration labels are clean. In many AI deployment

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MENO: Memory-Efficient Neural Operator

DGX agent

arXiv:2609.27739v1 Announce Type: new Abstract: We propose the Memory-Efficient Neural Operator (MENO) as a high-performance PDE neural solver based on the Manifold Function Encoder (MFE). MENO featur

researcharxiv-cs-lg

24 Sept 2026

MicroQonv: Reshaping Convolution Tensors for Efficient Microscaling in Training and Inference

arXiv:2609.28358v1 Announce Type: cross Abstract: Microscaling quantization techniques are increasingly used to represent neural network parameters with 8 bits or fewer while preserving near-full prec

MotionSpec: Spectral Trajectory Supervision for Motion-Consistent Video Generation

arXiv:2609.28095v1 Announce Type: new Abstract: Recent advances in text-to-video generation have enabled high-fidelity visual synthesis, yet realistic motion remains challenging. Generated videos may

Motoneuron-Inspired Sampling for Model Predictive Path Integral Control

arXiv:2609.28325v1 Announce Type: new Abstract: Model Predictive Path Integral (MPPI) control relies on stochastic trajectory sampling, and its performance under limited rollout budgets depends strong

Multi-View Fusion for Encrypted C2 Detection: A Leakage-Controlled Measurement Study of Evaluation Pitfalls

arXiv:2609.27311v1 Announce Type: cross Abstract: Command-and-control (C2) traffic increasingly hides within TLS, so defenders now apply machine learning to traffic metadata. Many studies assume that

Multimodal Voice Activity Projection for Social Robot Mediation: Expected Behavior and Deployment Constraints

arXiv:2609.28317v1 Announce Type: new Abstract: Turn-taking prediction is especially relevant for social robots that act as mediators in human-human interaction, where the expected action is often not

Multitask Regression with Pairwise Fusion

arXiv:2609.27280v1 Announce Type: cross Abstract: We study multitask regression when coefficient sharing can differ by predictor. For a given predictor, many tasks may have the same coefficient while

NaviScale: Generating Large-Scale Semantic Map Datasets for Object Navigation

arXiv:2609.27218v1 Announce Type: new Abstract: Embodied navigation requires spatial representations that generalize across unseen environments, yet collecting large amounts of annotated data from rea

NeuralSRNF: Neural Square Root Normal Fields for the Statistical Shape Analysis and Generation of Nonrigid 3D and 4D Objects

arXiv:2609.27728v1 Announce Type: new Abstract: We introduce NeuralSRNF, a novel framework for the statistical shape analysis and generation of genus-zero 3D and 4D objects that undergo nonrigid defor

NGN: Learning Neural Network Size as a Differentiable Count

arXiv:2609.27291v1 Announce Type: new Abstract: Neural network size is usually chosen before training, separating architecture selection from weight optimization. We introduce the Neurogenesis Network

Nonequilibrium Phases of Repulsive Self-Attention: Chaos, Attention Condensation, and Emergent Locality

arXiv:2609.28448v1 Announce Type: cross Abstract: We study the nonequilibrium dynamics of a minimal recurrent transformer with N normalized tokens, Q=K=I, and a negative value map V=-I. Similarity-bas

Omnidirectional Amphibious Locomotion via Internal Mass Actuation

arXiv:2609.27358v1 Announce Type: new Abstract: Field robots must traverse varied terrain and obstacles while remaining robust to water, debris, vegetation, and physical contact. We present MARBLE, a

On the Diffusibility of High-Dimensional Latents

arXiv:2609.28473v1 Announce Type: new Abstract: Representation Autoencoders (RAEs) enable diffusion models to operate in the feature spaces of pretrained visual encoders. However, many off-the-shelf e

Optimizing watermarks for large language models

arXiv:2312.17295v2 Announce Type: replace-cross Abstract: With the rise of large language models (LLMs) and concerns about potential misuse, watermarks for generative LLMs have recently attracted much

Order-Invariant Answers, Order-Sensitive Representations in Mathematical Reasoning

arXiv:2609.28442v1 Announce Type: cross Abstract: Reordering a set of mathematical rules without changing its meaning should preserve the correct answer, but must a model's internal representations st

Overlapping Visual Grouping Without Semantic Priors

arXiv:2609.27423v1 Announce Type: new Abstract: Most computer-vision systems organize visual input toward a predefined interpretation, such as semantic categories, prompted regions, learned object-lik

Passing: An Endless Journey through Reconstructed Spacetime with AI-Generated Sound

arXiv:2609.27489v1 Announce Type: cross Abstract: This paper introduces Passing, an interactive audiovisual installation that generates an endless journey from a single continuous monorail-window reco

Pheno-GS: Phenoscape-scale Geodesic Sinkhorn

arXiv:2609.27633v1 Announce Type: new Abstract: High-throughput single-cell data is now collected across large patient cohorts. Understanding patient-level heterogeneity from cellular-level data motiv

PhyMo: A Physical-Field Modality for Multimodal AI4Physics

arXiv:2609.27554v1 Announce Type: cross Abstract: Multimodal learning is emerging as a powerful paradigm for AI for Physics (AI4Physics), where predicting physical systems requires the joint interpret

Physiologically Informed Digital Auscultation for Pneumonia Detection in Long-term Care Residents

arXiv:2609.27222v1 Announce Type: cross Abstract: Pneumonia is difficult to diagnose in older long-term care residents; multimorbidity and atypical presentations obscure signs, motivating operationall

PISCES: Physics-Informed Solar-wind Convolutional autoEncoder for Space-weather Anomaly Detection and Early Warning

arXiv:2609.28022v1 Announce Type: cross Abstract: Space weather early warning depends on detecting solar wind transients in in-situ measurements at the first Sun-Earth Lagrange point (L1), before they

Planning Trajectories that Bounce: Reflection Classes for Collision-Tolerant Robots

arXiv:2609.27145v1 Announce Type: new Abstract: Robot navigation methods tend to avoid contact, and consequently search for collision-free trajectories. For robots with high inertia and limited maneuv

Pose-Aware Multimodal Automatic Tagging for Greek Traditional Music

arXiv:2609.27094v1 Announce Type: cross Abstract: Automatic tagging is a core task in Music Information Retrieval (MIR), yet most tagging systems exploit only audio. Live music performance is inherent

Predicting Quantization Price for Selecting PTQ Configurations Before Deployment

arXiv:2609.28270v1 Announce Type: new Abstract: Weight-space post-training quantization (PTQ) must choose finite formats, granularities, quantizer families, transformations, and bits before the comple

researcharxiv-cs-cl

Predicting the Progression of Adolescent Idiopathic Scoliosis

arXiv:2609.28434v1 Announce Type: new Abstract: Adolescent Idiopathic Scoliosis is defined as a lateral curvature of the spine that develops during adolescence, without known cause. The condition can

Prediction with Expert Advice: Anytime Regret with Many Experts Matches the Fixed-Time Constant

arXiv:2609.27206v1 Announce Type: cross Abstract: Prediction with expert advice is a fundamental problem in online learning. When the time horizon T is known in advance, the minimax cumulative regret

Probabilistic and Geometry Aware Neural Surrogate of Scrape Off Layer Plasma Simulations

arXiv:2609.28116v1 Announce Type: new Abstract: Fast surrogates for tokamak boundary-plasma simulation are typically deterministic regressors mapping a global operating point to a flattened vector of

Quality over Quantity: Semi-Supervised Detection of Illicit Bitcoin Flows via Feature Engineering

arXiv:2609.27936v1 Announce Type: new Abstract: Detecting illicit cryptocurrency transactions is hampered by extreme class imbalance, adversarial obfuscation, and a scarcity of reliable labels. While

Quantization-Robust Unlearning through the Lens of Retain-Forget Loss Landscapes Interaction

arXiv:2609.27355v1 Announce Type: cross Abstract: Unlearning ensures LLM compliance by removing the influence of private or copyrighted training data. However, since LLM models typically undergo post-

QUARTET: Quad-branch cross-Attention and Random-walk Traces for Enhancing Transformers on Relational Graphs

arXiv:2609.26855v1 Announce Type: cross Abstract: Relational Deep Learning (RDL) models multi-table databases as heterogeneous temporal graphs, and graph transformers currently achieve state-of-the-ar

Query Implied Generative Engine Optimization

arXiv:2609.27845v1 Announce Type: cross Abstract: The landscape of search has changed drastically with how people look for information online. Traditional search engines are being replaced by Generati

Quieter Than the Room: Representation Drift and Task Robustness in Speech Encoders

arXiv:2609.27195v1 Announce Type: cross Abstract: Non-speech interference can change a speech representation without causing comparable task loss. We test eight frozen encoders on four tasks, adding n

researcharxiv-cs-cl

Random Polytope Descriptors

arXiv:2009.13987v3 Announce Type: replace Abstract: We introduce a class of random polytopes which simultaneously generalizes several known constructions. While being fairly general, these polytopes a

Recursive Uncertainty-Gated Image Registration for Learning-based Algorithms

arXiv:2609.28081v1 Announce Type: cross Abstract: Conventional image registration algorithms are robust to domain shifts and achieve low errors, but they are slow and computationally expensive. Deep-l

Regular Fourier Features for Nonstationary Gaussian Processes

arXiv:2602.23006v3 Announce Type: replace-cross Abstract: Simulating a Gaussian process requires sampling from a high-dimensional Gaussian distribution, which scales cubically with the number of sampl

RelCheck: Dual-Evidence Spatial Grounding for VLM Hallucination Correction

arXiv:2609.27890v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) fre- quently generate text that is inconsistent with the input image. While object- and attribute-level hallu

Reliable Federated TinyML Deployment for IoT Security

arXiv:2609.27202v1 Announce Type: cross Abstract: The growing deployment of Internet of Things (IoT) devices has increased the need for privacy-preserving intrusion detection systems that operate dire

Reliable Fusion of Conflicting Experts

arXiv:2609.27913v1 Announce Type: new Abstract: We study the problem of aggregating opinions from multiple black-box experts in noisy, conflict-prone settings where expert reliability varies across in

Resource-Adaptive Stochastic Gradient Descent for Online Linear Programming without Re-solving

arXiv:2609.28263v1 Announce Type: new Abstract: The growth of large language model (LLM) inference and search services increases the scale of online linear programming problems, motivating computation

Retrieval Augmented (Knowledge Graph), and Large Language Model-Driven Design Structure Matrix (DSM) Generation of Cyber-Physical Systems

arXiv:2602.16715v2 Announce Type: replace Abstract: We explore the potential of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Graph-based RAG (GraphRAG) for generating Design

Robustness of Diffusion Models under Distribution Shift

arXiv:2609.27546v1 Announce Type: cross Abstract: Score-based diffusion models are increasingly considered in settings where the underlying data distribution may differ from the training distribution,

Rolling Conformal Prediction in Sequential Model Training

arXiv:2609.26951v1 Announce Type: cross Abstract: We introduce Rolling Conformal Prediction (rolling-CP), a distribution-free predictive inference method for the setting of sequential model training.

ScoutNeRV: Rapid Encoding of Grid-Based Video INRs via ScoutNet

arXiv:2609.27958v1 Announce Type: new Abstract: Implicit neural representations (INRs) have emerged as a promising paradigm for video compression, providing compact neural representations with flexibl

Self-Improvement as Coherence Optimization: A Theoretical Account

arXiv:2601.13566v2 Announce Type: replace-cross Abstract: Can language models improve their accuracy without external supervision? Methods such as debate, bootstrap, and internal coherence maximizatio

Semantic-Guided Fusion Network for Multi-Source Remote Sensing Image Classification

arXiv:2609.27854v1 Announce Type: cross Abstract: Multi-source remote sensing image classification has attracted increasing attention due to the complementary spectral, structural, and geometric infor

Shared Global KV with Layer-Specific Local History

arXiv:2609.28006v1 Announce Type: new Abstract: Decoder-only Transformer language models cache keys and values (KV) to reuse past computation during generation. Sharing KV across layers saves storage

Sharp Convergence of Wasserstein Gradient Flows for Spectrally Nonnegative Interaction Energies

arXiv:2609.27008v1 Announce Type: cross Abstract: We study the long-time behavior of Wasserstein gradient flows for interaction energies [ mathsf E[mu] = frac12iint_{Mimes M}K(x,y),mathrm dmu(x),mathr