Search: “applications”

Generative AI-Based Data Augmentation for Oral Lesion Classification: The PhotoMOCI Dataset and Benchmark

arXiv:2609.35226v1 Announce Type: new Abstract: Early detection of oral cancer via photographic imaging presents a promising avenue for large-scale oral cavity screening. However, the development of r

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Geometric Identification in Predict-Then-Optimize Learning

DGX agent

arXiv:2609.33472v1 Announce Type: new Abstract: Decision-focused surrogates can recover downstream decisions without identifying the quotient report. We characterize the equality set of the convex Sma

researcharxiv-cs-lg

29 Sept 2026

High-Level Text Preprocessing for Semantic Similarity Analysis of Discursive Texts: A Framework and Empirical Demonstration

arXiv:2609.33983v1 Announce Type: cross Abstract: Semantic Textual Similarity (STS) methods assume that a document's lexical content faithfully represents what it asserts. This assumption fails for di

High-Probability Guarantees for SGD under eta-Heavy-Tailed Gradient Noise

arXiv:2609.32195v1 Announce Type: cross Abstract: Stochastic gradient descent (SGD) is widely used to train machine learning models, but subsampling the training data introduces noise into its updates

How Much Imprecision is Enough Imprecision in my Classifier? A Practical Elicitation Procedure

arXiv:2609.33352v1 Announce Type: new Abstract: Set-valued classifiers, whether derived from precise probabilities and an adapted cost function, from convex sets with a robust inference mechanism, or

HUMAN-TCI: Hierarchical Multi-Stream Motion-Aware Network with Torso-Centered Interaction for Text-to-Motion Retrieval

arXiv:2609.34430v1 Announce Type: new Abstract: Accurate retrieval of human motions is a crucial first step in text-guided human motion modeling and synthesis, as it selects semantically relevant sequ

Agents

Improving Causal Effect Estimation of Weighted RegressionBased Estimator using Neural Networks

arXiv:2110.15075v2 Announce Type: replace Abstract: Estimating causal effects from observational data informs us about which factors are important in an autonomous system, and enables us to take bette

agentsarxiv-cs-lg

Lagrangian--Hamiltonian Flows for Video Prediction and Image Generation: A Symplectic Perspective

arXiv:2609.35710v1 Announce Type: new Abstract: We introduce LHFM, a geometric framework for learning image dynamics. Drawing on structures central to classical mechanics, symplectic geometry, and geo

lapanda: A Matrix-Free Differentiable Solver for Nonconvex Constrained Optimization Layers

arXiv:2609.33630v1 Announce Type: cross Abstract: Differentiable optimization brings the structural guarantees of mathematical optimization to network pipelines, allowing them to be trained end-to-end

Hardware

Learned Preconditioning for a Primal-Dual Interior-Point Method

arXiv:2609.35665v1 Announce Type: cross Abstract: Interior-point methods (IPMs) are among the most widely used algorithms for constrained optimization, yet their Newton-based search directions require

hardwarearxiv-cs-lg

Learning Transferable Sensor Models via Language-Informed Pretraining

arXiv:2603.11950v2 Announce Type: replace-cross Abstract: Multimodal language models have demonstrated strong semantic understanding and reasoning over physiological and behavioral signals captured fr

Learning When to Recur: Token-Adaptive Recursion for Imbalanced Ophthalmic Domain Incremental Learning

arXiv:2609.32785v1 Announce Type: cross Abstract: Domain incremental learning is essential for adapting ophthalmic deep learning models to sequential clinical domains while preserving diagnostic exper

Localized time-frequency representation learning for bioacoustic classification in complex soundscapes

arXiv:2502.13440v2 Announce Type: replace-cross Abstract: Prevailing bioacoustic classifiers assign species labels to fixed time-frequency windows rather than to individual vocalizations. When multipl

local-aiarxiv-cs-cv

Logic Gate Networks and Lookup Table Networks as Lightweight Hardware Classifiers for Inter-patient ECG Arrhythmia Classification

arXiv:2609.32854v1 Announce Type: new Abstract: Deep Differentiable Logic Gate Networks (LGNs) and Lookup Table Networks (LUTNs) offer a promising approach for very low power inference due to their us

Look Before You Judge: Training-Free Region Mining for Grounded and Explainable Deepfake Detection

arXiv:2609.35536v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can explain deepfake verdicts in natural language, but such explanations are not necessarily visually grounded

MaD-RL: Matching Distributions for Calibrating LLMs with Reinforcement Learning

arXiv:2609.31644v1 Announce Type: new Abstract: Reinforcement learning (RL) is widely used in language-model post-training to maximize rewards assigned to individual model outputs, such as scores from

MAESTRO: a Multimodal Auditory-attention Egocentric Speech-TRacking Open corpus

arXiv:2609.31898v1 Announce Type: cross Abstract: Humans rely on gaze, head movements, and visual cues to attend to speakers in noisy environments, yet auditory attention decoding (AAD) has been studi

MorphAtt: A Neuromorphic Accelerator for Efficient Multi-Head Attention Processing in Spiking Vision Transformers

arXiv:2609.33207v1 Announce Type: cross Abstract: Spiking Vision Transformers (SViTs) are developed as an energy-efficient alternative to conventional ViTs for computer vision tasks at the edge. Howev

MW-Nowcast: Six-hour ensemble nowcasting of extreme precipitation

arXiv:2609.34836v1 Announce Type: cross Abstract: Extending reliable nowcasting of extreme precipitation could provide critical additional time for warnings and emergency response during high-impact e

local-aiarxiv-cs-lg

Not Every Term Adds New Structure: Sobolev Novelty for Symbolic Regression

arXiv:2609.32597v1 Announce Type: new Abstract: Symbolic regression (SR) aims to discover compact and meaningful mathematical equations from data, but searching the vast combinatorial space of symboli

Notes on Generative Modeling for Feedback Control and Planning

arXiv:2609.33164v1 Announce Type: cross Abstract: In these notes, we view control as a dynamically constrained sampling problem on the state-space of a control system. With this viewpoint, we extend m

On the Numerical Reliability of Differentiable Physics-Based Optimization for Robotic Material Manipulation

arXiv:2609.34666v1 Announce Type: cross Abstract: Differentiable physics is increasingly used in robotic material manipulation for system identification, trajectory or skill optimization, demonstratio

Patch Rebirth: Toward Fast and Transferable Model Inversion of Vision Transformers

arXiv:2509.23235v2 Announce Type: replace Abstract: Model inversion is a widely adopted technique in data-free learning that reconstructs synthetic inputs from a pretrained model through iterative opt

Physics-Informed Neural Networks with Architectural Physics Embedding for Large-Scale Wave Field Reconstruction

arXiv:2603.02231v2 Announce Type: replace Abstract: Large-scale wave field reconstruction requires precise solutions but faces challenges with computational efficiency and accuracy. The physics-based

PrismQuant: Optimal Null-Space Rotations for Grouped Quantizers

arXiv:2609.32429v1 Announce Type: cross Abstract: Smaller activation outliers do not necessarily imply better low-bit quantization: their alignment with the quantizer matters. We introduce PrismQuant,

QuacamFM: Quaternion-Constrained Flow Matching for Camera Pose Estimation

arXiv:2609.32455v1 Announce Type: new Abstract: Camera pose estimation from multi-view images remains a challenge in computer vision. Traditional methods often address this problem using Structure-fro

Quantifying How Training Gradient Sparsity Affect Spiking Neural Network Accuracy And Robustness

arXiv:2509.23762v4 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) have recently received increasing attention in both computational neuroscience and artificial intelligence owin

REALM: A Coarse-to-Fine Generative Framework for Embodied Reactive Listening

arXiv:2609.33095v1 Announce Type: new Abstract: Generating responsive listener facial motion is an important task for embodied conversational AI. Two modeling challenges are central: accounting for th

local-aiarxiv-cs-ro

Reliable Replay through Spatial Coherence in Online Continual Learning

arXiv:2609.33725v1 Announce Type: cross Abstract: Continually adapting models to new tasks requires retaining earlier knowledge under limited memory and computation. Experience replay addresses this c

Representation Editing for Multimodal Test-Time Adaptation

arXiv:2609.32263v1 Announce Type: new Abstract: Multimodal test-time adaptation (TTA) aims to adapt a pretrained multimodal model online to distribution shift across modalities using unlabeled test da

ResonAct: Streaming Metrics for Runtime Diagnosis and Self-Healing in Multi-Agent Systems

arXiv:2609.34701v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used to automate enterprise workflows involving multiple specialized agents, external tools, and long-runni

local-aiarxiv-cs-lg

Robot-Assisted Deployment and Maintenance of Inflatable Modules for Lunar Habitation: A Field Demonstration

arXiv:2609.34498v1 Announce Type: new Abstract: Long-term human habitation and in-situ development on the Moon open a new era of space utilization. In this context, robots are a key technology for fac

safetyarxiv-cs-ro

Robust Peak-cost Constrained Reinforcement Learning

arXiv:2607.15457v2 Announce Type: replace Abstract: We study robust peak-cost constrained reinforcement learning (ours), where the objective is to maximize expected reward while controlling the maximu

Scalable GNN-based Knowledge Graph Representation Learning with Efficient Message Passing

arXiv:2609.34499v1 Announce Type: new Abstract: Graph neural networks (GNNs) excel at representation learning on Knowledge Graphs (KGs), achieving stateof-the-art performance on tasks like link predic

SceneScaffold: Active Scene-State Construction for Unified 3D Scene Understanding

arXiv:2609.33518v1 Announce Type: new Abstract: Recent 3D large multimodal models (3D-LMMs) rely on a visual bottleneck to compress complex 3D scene evidence into a limited number of visual tokens com

Hardware

Scope-WM: Scoped Computation for Efficient Visual World Models

arXiv:2609.33218v1 Announce Type: new Abstract: Visual world models enable robotic planning by predicting future observations, but dense latent-state propagation and sample-intensive trajectory optimi

hardwarearxiv-cs-cv

Self-Reconstruction Dynamics for Autoencoder Reconstruction Refinement

arXiv:2609.32268v1 Announce Type: new Abstract: Standard autoencoder (AE) inference uses a single encoder-decoder pass, though the latent may not be optimal for each sample under a fixed decoder. We a

Tutorials

SeLMRoute: Probabilistic Semantic Evidence for Large Language Model Routing

arXiv:2609.34736v1 Announce Type: cross Abstract: Large language model (LLM) routing aims to select the most suitable model for each incoming query. Most existing routers learn this decision directly

tutorialsarxiv-cs-lg

Simulation for Planetary Robotic Perception and Autonomy: A Concise Survey of Recent Capabilities and Gaps

arXiv:2609.34743v1 Announce Type: new Abstract: Planetary robotics is an important enabler of scientific exploration in environments where direct human-in-the-loop operation is costly, hazardous, or i

researcharxiv-cs-ro

Skeletons in Flow: Graph Structured Flow Matching for Human Motion Prediction

arXiv:2609.32231v1 Announce Type: new Abstract: Human motion prediction requires diverse future trajectories that remain consistent with observed motion and the articulated physical structure of the b

Soft Geometric Inductive Bias for Object Centric Dynamics

arXiv:2512.15493v2 Announce Type: replace Abstract: Physical systems are naturally parameterized in terms of geometric entities and their transformations. While exact equivariance can be a powerful in

Spectral Super-Resolution using Spatial-Spectral Residual Operator Networks

arXiv:2609.35410v1 Announce Type: new Abstract: Spectral super-resolution of multispectral satellite images can enable high temporal- and spatial-resolution hyperspectral satellite imagery at a modest

Sub-Model Short-Term Memory Convolutions for Keyword Spotting Systems on Device

arXiv:2609.35005v1 Announce Type: cross Abstract: Keyword Spotting (KWS) is becoming increasingly important as voice-controlled devices grow more widespread. While voice interaction with smartphones a

SymDrift: One-Shot Generative Modeling under Symmetries

arXiv:2605.06140v2 Announce Type: replace Abstract: Generative modeling of physical systems, such as molecules, requires learning distributions that are invariant under global symmetries, such as rota

Synthetic Thermal Image Generation for Real-Time Animal Detection Under Low-Visibility Conditions

arXiv:2609.32944v1 Announce Type: new Abstract: Wildlife-vehicle collisions remain a significant road safety concern, particularly during nighttime and low-visibility conditions when RGB-based percept

safetyarxiv-cs-cv

TACO: Training-free Sound Prompted Segmentation via Semantically Constrained Audio-visual CO-factorization

arXiv:2412.01488v4 Announce Type: replace-cross Abstract: Large-scale pre-trained audio and image models demonstrate an unprecedented degree of generalization, making them suitable for a wide range of

Tutorials

The Geometry of Logic: Stratification Induces Semantic Structure and Robust Reasoning

arXiv:2609.32927v1 Announce Type: new Abstract: Transformer-based language models perform well on symbolic tasks, yet it remains unclear whether they learn generalizable rules or rely on statistical s

tutorialsarxiv-cs-lg

Training Witnesses: Trusting the Training without Trusting the Trainer

arXiv:2609.33915v1 Announce Type: new Abstract: Progress in machine learning cannot outpace our ability to verify it. With an explosion in papers today, every scientific claim rests initially on trust