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Newest papers, page 132
GM-GReFEL: Geometry-Guided Spatiotemporal State-Space Learning for Robust Dynamic Facial Expression Recognition
Recognizing facial expressions in unconstrained video suffers from two coupled problems: self-attention grows quadratically in cost with clip length, and crowdsourced labels are noisy.PriMa-Causa: Causal Prescriptive Maintenance
Automated manufacturing requires data-driven decisions under uncertainty and sparse observational records, and unplanned downtime is a dominant cost of getting them wrong.Prompt Sensitivity in Tool-Augmented Model Comparisons
Language models are compared on question-answering benchmarks that pose each question in one wording, and a reworded question can change which of two models scores higher.Towards Field-Deployable Wearable IMU Systems for Occupational Activity Recognition
Wearable inertial measurement unit (IMU) systems for construction worker human activity recognition (HAR) routinely report aggregate accuracies above 95 %, rarely under genuine subject-independent…Prediction Uncertainty Controlled Computer Model Calibration
Computer-model calibration is usually undertaken in service of prediction, yet neither Bayesian Kennedy-O'Hagan (KOH) calibration nor amortized simulation-based inference is built to control the…Memory before Goal: Role of Pre-History Memory for Humanoid Loco-Manipulation
Humanoid loco-manipulation in dynamic scenes is non-Markovian: cues vanish as objects change or are hidden, or leave the view as the robot turns and walks, yet whole-body vision-language-action…Prompting Strategy Effects Depend on the Judge: A Multilingual Study of LLM-as-a-Judge Robustness
LLM-as-a-Judge evaluation is increasingly applied to multilingual tasks, yet prompting strategies such as Chain-of-Thought and Role Conditioning are recommended based solely on English benchmarks.Track finding and particle identification performance with particle physics foundation models
Modern high energy nuclear and particle physics experiments produce large amounts of sparse data that must be reduced significantly in size before performing physics analysis.RaSFNet: Ray-aligned and Scan-aware Fusion Network for LiDAR Semantic Segmentation
LiDAR point cloud semantic segmentation is a fundamental component of 3D perception for autonomous driving and robotics.When More Metadata Misleads: Probing Field-Level Grounding in LLM-Generated Museum Descriptions
Metadata-conditioned generation is often framed as a data-to-text task in which additional input fields should improve grounding.Inside-JEPA: From Prediction to Relational Grounding in Latent World Models
Joint-embedding predictive architectures (JEPAs) learn world models in latent space, enabling efficient planning but leaving their states opaque.Evolving Federated Density Peak Clustering with Shuffler-Based Anonymization
In this paper, we present a novel one-shot federated clustering approach based on evolving fuzzy clustering and shuffler-based anonymization.Local Discrimination of Binary Classifiers via Localized AUC Functional
Risk prediction models are frequently evaluated with AUC, which means that during evaluation we are blind to performance heterogeneity, which could lead to bad decision-making in clinics.Muting Tokens: Exploring Token Sparsification for Efficient Audio Transformers
Transformer-based models have shown strong performance across diverse tasks, but their reliance on self-attention mechanisms often leads to high computational costs.QuaNAS: Uncertainty-Aware Reuse of Earlier Searches for Query-Efficient Neural Architecture Search
Neural architecture search (NAS) on a new dataset often affords only tens of short training runs, so what the search knows before its first evaluation decides its efficiency.Can Entanglement-Induced Feature-Map Designs Improve Projected Quantum Kernels?
Projected quantum kernels (PQKs) have emerged as a notable approach to circumvent the hardness of machine learning tasks arising from the exponential dimensionality of the quantum Hilbert space.Deep ReLU Networks Can Fail the Best Approximation Property for Continuous Target Functions
We construct a continuous function on $[-1,1]^2$ for which the infimum of the $L^2$-approximation error over the class of ReLU networks with two hidden layers and architecture $(2,2,1,1)$ is not…Learning Robot Behavior Priors from Non-Robotic Synthetic Data
Real robot data, rich across tasks and morphologies, is often treated as the bottleneck for training robot learning models, including embodied foundation models that aim for zero-shot physical…Beyond Accuracy: Disentangling Decomposition from Typed-State Quality Assurance in Multi-Agent LLM Pipelines
Multi-agent LLM pipelines are often credited with gains in software engineering tasks, but it is rarely clear whether a gain stems from the typed contract between agents or from the specialized…DISC: Domain-Integrated Similarity Cost for Time-Series Dataset
The growth of time-series datasets and foundation models has made dataset comparison a central part of time-series workflows.