Search: “applications”

The Recovery Mechanism: Technology, Education, and What Happens When the Pattern Breaks

arXiv:2605.16283v1 Announce Type: cross Abstract: For centuries, each new technology has automated some layer of cognitive work and been absorbed by education retreating upward to teach the skills mac

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Applications

Thermal-Only Crowd Counting with Deployment-Time Privacy Protection

DGX agent

arXiv:2605.17042v1 Announce Type: new Abstract: While RGB-Thermal crowd counting has shown promise, the paradigm faces critical limitations: RGB data raises privacy concerns in public surveillance, an

applicationsarxiv-cs-cv

19 May 2026

Traces of Social Competence in Large Language Models

arXiv:2603.04161v2 Announce Type: replace Abstract: The False Belief Test (FBT) has been the main method for assessing Theory of Mind (ToM) and related socio-cognitive competencies. For Large Language

Tracking Drift: Variation-Aware Entropy Scheduling for Non-Stationary Reinforcement Learning

arXiv:2601.19624v2 Announce Type: replace-cross Abstract: Real-world reinforcement learning often faces environment drift, but most existing methods rely on static entropy coefficients/target entropy,

Training data attribution in diffusion models via mirrored unlearning and noise-consistent skew

arXiv:2605.17938v1 Announce Type: cross Abstract: Training data attribution (TDA) should enable generative model interpretability and foster a variety of related downstream tasks. Nonetheless, current

Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights

arXiv:2505.03205v3 Announce Type: replace Abstract: Transformers serve as the foundational architecture for large language and video generation models, such as GPT, BERT, SORA and their successors. Em

Uncertainty Quantification as a Principled Foundation for Explainable Artificial Intelligence: A Case Study of Counterfactual Explanations

arXiv:2502.17007v2 Announce Type: replace-cross Abstract: In this paper we argue that, to its detriment, transparency research overlooks many foundational concepts of artificial intelligence. As an il

Universal Time-Series Representation Learning: A Survey

arXiv:2401.03717v4 Announce Type: replace-cross Abstract: Time-series data exists in every corner of real-world systems and services, ranging from satellites in the sky to wearable devices on human bo

UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities

arXiv:2504.20734v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has shown substantial promise in improving factual accuracy by grounding model responses with external kn

Unveiling Memorization-Generalization Coexistence: A Case Study on Arithmetic Tasks with Label Noise

arXiv:2605.18022v1 Announce Type: cross Abstract: Highly over-parameterized models can simultaneously memorize noisy labels and generalize well, yet how these behaviors coexist remains poorly understo

Research

Virtues of Ordered Chaos: Planning with Topple Actions in Tabletop Stack Rearrangement

arXiv:2605.17815v1 Announce Type: cross Abstract: Efficient object manipulation strategies have significant impact in automation applications. In this work, the stack rearrangement in tabletop setting

researcharxiv-cs-ai

VISAFF: Speaker-Centered Visual Affective Feature Learning for Emotion Recognition in Conversation

arXiv:2605.18547v1 Announce Type: new Abstract: Emotion Recognition in Conversation (ERC) is essential for effective human-machine interaction, aiming to identify speakers' emotional states in multi-t

VVitCutLER: Towards Unsupervised Object Detection and Segmentation in Videos

arXiv:2605.17584v1 Announce Type: new Abstract: Unsupervised pixel-level video understanding remains challenging in real-world scenarios, where motion blur, occlusion, and fast object dynamics often c

Weakly Supervised Cross-Modal Learning for 4D Radar Scene Flow Estimation

arXiv:2605.18507v1 Announce Type: new Abstract: Due to the difficulty of obtaining ground-truth data for 4D radar scene flow estimation, previous methods typically rely on either self-supervised losse

What Drives Success in Physical Planning with Joint-Embedding Predictive World Models?

arXiv:2512.24497v3 Announce Type: replace Abstract: A long-standing challenge in AI is to develop agents capable of solving a wide range of physical tasks and generalizing to new, unseen tasks and env

XCTFormer: Leveraging Cross-Channel and Cross-Time Dependencies for Enhanced Time-Series Analysis

arXiv:2605.18534v1 Announce Type: new Abstract: Multivariate time-series analysis involves extracting informative representations from sequences of multiple interdependent variables, supporting tasks

A Cascaded Generative Approach for e-Commerce Recommendations

arXiv:2605.11118v2 Announce Type: replace Abstract: Personalized storefronts in large e-commerce marketplaces are often assembled from many independent components: static themes per page section ('pla

A Scalable Nonparametric Continuous-Time Survival Model through Numerical Quadrature

arXiv:2605.16208v1 Announce Type: cross Abstract: Flexible continuous-time survival modeling is critical for capturing complex time-varying hazard dynamics in high-dimensional data; however, training

Adesua: Development and Feasibility Study of an AI WhatsApp Bot for Science Learning in West Africa

arXiv:2605.15376v1 Announce Type: new Abstract: Sub-Saharan Africa faces persistently high student-teacher ratios and shortages of qualified teachers, limiting students' access to personalized learnin

ADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checking

arXiv:2510.13842v2 Announce Type: replace-cross Abstract: Knowledge poisoning poses a critical threat to Retrieval-Augmented Generation (RAG) systems by injecting adversarial content into knowledge ba

Calibrating LLMs with Semantic-level Reward

arXiv:2605.15588v1 Announce Type: new Abstract: As large language models (LLMs) are deployed in consequential settings such as medical question answering and legal reasoning, the ability to estimate w

Can Vision Language Models Be Adaptive in Mathematics Education? A Learner Model-based Rubric Study

arXiv:2605.16011v1 Announce Type: cross Abstract: Adaptive learning refers to educational technologies that track learners' learning progress and adapt the instructional process based on individual le

Defining Cultural Capabilities for AI Evaluation: A Taxonomy Grounded in Intercultural Communication Theory

arXiv:2605.15990v1 Announce Type: new Abstract: Tremendous efforts have been put into evaluating the inclusivity and effectiveness of AI systems across cultures. However, the cultural capabilities con

Does Theory of Mind Improvement Really Benefit Human-AI Interactions? Empirical Findings from Interactive Evaluations

arXiv:2605.15205v1 Announce Type: new Abstract: Improving the Theory of Mind (ToM) capability of Large Language Models (LLMs) is crucial for effective social interactions between these AI models and h

Domain-Independent Game Abstraction using Word Embedding Techniques

arXiv:2605.15543v1 Announce Type: cross Abstract: Many games of interest in the real world are often intractably large, thereby necessitating the use of game abstraction to shrink them in size, typica

ExplainerPFN: Towards tabular foundation models for model-free zero-shot feature importance estimations

arXiv:2601.23068v2 Announce Type: replace-cross Abstract: Computing the importance of features in supervised classification tasks is critical for model interpretability. Shapley values are a widely us

FedOptima: Optimizing Resource Utilization in Federated Learning

arXiv:2504.13850v2 Announce Type: replace-cross Abstract: Federated learning (FL) systems facilitate distributed machine learning across a server and multiple devices. However, FL systems have low res

FM-G-CAM: A Holistic Approach for Explainable AI in Computer Vision

arXiv:2312.05975v3 Announce Type: replace-cross Abstract: Explainability is a vital aspect of modern AI for real-world impact and usability. The main objective of this paper is to emphasise the need t

Fortress: A Case Study in Stabilizing Search Recommendations via Temporal Data Augmentation and Feature Pruning

arXiv:2605.15299v1 Announce Type: cross Abstract: In search and recommendation systems, predictive models often suffer from temporal instability when certain input features introduce volatility in out

Greedy or not, here I come: Language production under vocabulary constraints in humans and resource-rational models

arXiv:2605.15365v1 Announce Type: new Abstract: Communicating using only a limited vocabulary is a common but challenging cognitive phenomenon, requiring an ideal communicator to plan carefully to opt

ITGPT: Generative Pretraining on Irregular Timeseries

arXiv:2605.16069v1 Announce Type: new Abstract: Timeseries regression models often struggle to leverage large volumes of labeled multimodal data, particularly when the data are irregularly sampled or

LAPS: Improving Incremental LiDAR Mapping using Active Pooling and Sampling for Neural Distance Fields

arXiv:2605.15496v1 Announce Type: cross Abstract: Neural distance fields offer a compact and continuous representation of 3D geometry, making them attractive for incremental LiDAR mapping. However, th

Research

Layer Selection in Feature-Based Losses Affects Image Quality and Microstructural Consistency in Deep Learning Super-Resolution of Brain Diffusion MRI

arXiv:2605.15895v1 Announce Type: cross Abstract: Clinical application of high-resolution diffusion MRI is hindered by hardware limitations and prohibitive scan times, motivating computational super-r

researcharxiv-cs-cv

Layer-wise Derivative Controlled Networks

arXiv:2605.15463v1 Announce Type: new Abstract: As machine learning models grow in complexity, they increasingly struggle with three conflicting demands: the need for high accuracy, the requirement fo

Learning Dynamic Pick-and-Place for a Legged Manipulator

arXiv:2605.15713v1 Announce Type: cross Abstract: Legged manipulators extend robotic capabilities beyond static manipulation by integrating agile locomotion with versatile arm control. However, achiev

Logical Grammar Induction via Graph Kolmogorov Complexity: A Neuro-Symbolic Framework for Self-Healing Clinical Data Integrity

arXiv:2605.15242v1 Announce Type: new Abstract: The reliability of Healthcare Information Systems (HIS) is frequently compromised by human-induced data entry errors, which existing statistical anomaly

Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing

arXiv:2509.20349v3 Announce Type: replace Abstract: Accurate time-series forecasting for complex physical systems is the backbone of modern industrial monitoring and control, yet deep learning models

RealRep: Generalized SDR-to-HDR Conversion via Attribute-Disentangled Representation Learning

arXiv:2505.07322v4 Announce Type: replace Abstract: High-Dynamic-Range Wide-Color-Gamut (HDR-WCG) technology is becoming increasingly widespread, driving a growing need for converting Standard Dynamic

Reasoners or Translators? Contamination-aware Evaluation and Neuro-Symbolic Robustness in Tax Law

arXiv:2605.16052v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have significantly enhanced automated legal reasoning. Yet, it remains unclear whether their performance

Reweighting free energy profiles between universal machine learning interatomic potentials for fast consensus building

arXiv:2605.15630v1 Announce Type: cross Abstract: Free energy profiles serve as a fundamental bridge between microscopic atomic fluctuations and macroscopic thermodynamic observables. Estimating the f

Toward World Modeling of Physiological Signals with Chaos-Theoretic Balancing and Latent Dynamics

arXiv:2605.15465v1 Announce Type: new Abstract: Physiological time series signals reflect complex, multi-scale dynamical processes of the human body. Existing modeling studies focus on static tasks su

Unified Simulation of Lagrangian Particle Dynamics via Transformer

arXiv:2605.15305v1 Announce Type: cross Abstract: A unified simulator that can model diverse physical phenomena without solver-specific redesign is a long-standing goal across simulation science. We p

Research

Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity

arXiv:2511.03606v2 Announce Type: replace-cross Abstract: The study of self-normalized processes plays a crucial role in a wide range of applications, from sequential decision-making to econometrics.

researcharxiv-cs-lg

Wind-Aware Optimal Trajectory Planning for Efficient Gliding of Fixed-Wing Aerial Systems

arXiv:2605.15619v1 Announce Type: new Abstract: Gliding offers small fixed-wing UAVs extended endurance and silent operation but requires accurate energy management, especially under wind disturbances

applicationsarxiv-cs-ro

A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights

arXiv:2511.05159v2 Announce Type: replace-cross Abstract: Convex clustering is a well-regarded clustering method, resembling the similar centroid-based approach of Lloyd's k-means, without requiring a

A Novel Schur-Decomposition-Based Weight Projection Method for Stable State-Space Neural-Network Architectures

arXiv:2605.14489v1 Announce Type: new Abstract: Building black-box models for dynamical systems from data is a challenging problem in machine learning, especially when asymptotic stability guarantees

Model Releases

A Problem-Oriented Taxonomy of Evaluation Metrics for Time Series Anomaly Detection

model-releasesarxiv-cs-ai

arXiv:2511.18739v2 Announce Type: replace Abstract: Time series anomaly detection is widely used in IoT and cyber-physical systems, yet its evaluation remains challenging due to diverse application ob

An Interpretable Latency Model for Speculative Decoding in LLM Serving

arXiv:2605.15051v1 Announce Type: new Abstract: Speculative decoding (SD) accelerates large language model (LLM) inference by using a smaller draft model to propose multiple tokens that are verified b