Search: “applications”

From Legal Text to Executable Decision Models: Evaluating Structured Representations for Legal Decision Model Generation

arXiv:2604.17153v1 Announce Type: new Abstract: Transforming legal text into executable decision logic is a longstanding challenge in legal informatics. With the rise of LLMs, this task has gained ren

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Applications

Frozen Vision Transformers for Dense Prediction on Small Datasets: A Case Study in Arrow Localization

DGX agent

arXiv:2604.16758v1 Announce Type: new Abstract: We present a system for automated detection, localization, and scoring of arrow punctures on 40,cm indoor archery target faces, trained on only 48 annot

applicationsarxiv-cs-cv

21 Apr 2026

FUSE: Ensembling Verifiers with Zero Labeled Data

arXiv:2604.18547v1 Announce Type: cross Abstract: Verification of model outputs is rapidly emerging as a key primitive for both training and real-world deployment of large language models (LLMs). In p

Geometric and Quantum Kernel Methods for Predicting Skeletal Muscle Outcomes in chronic obstructive pulmonary disease

arXiv:2601.00921v2 Announce Type: replace Abstract: Quantum methods are increasingly proposed for healthcare, but translational biomarker studies demand transparent benchmarking and robust small-datas

Gradient-Free Continual Learning in Spiking Neural Networks via Inter-Spike Interval Regularization

arXiv:2604.16496v1 Announce Type: cross Abstract: Continual learning, the ability to acquire new tasks sequentially without forgetting prior knowledge, is essential for deploying neural networks in dy

Grokking of Diffusion Models: Case Study on Modular Addition

arXiv:2604.17673v1 Announce Type: new Abstract: Despite their empirical success, how diffusion models generalize remains poorly understood from a mechanistic perspective. We demonstrate that diffusion

Horizon-Aware Forecasting of Passenger Assistance Demand for Rail Station Workforce Planning

arXiv:2604.16464v1 Announce Type: cross Abstract: Passenger assistance services are essential for accessible rail travel, yet demand varies substantially across stations and over time, creating challe

How Non-Linguistic Is the Indus Sign System? A Synthetic-Baseline Scorecard

arXiv:2604.17828v1 Announce Type: new Abstract: Whether the Indus Valley sign system (c. 2600-1900 BCE) encodes spoken language has been debated for decades. This paper introduces a multi-metric discr

How Training Data Shapes the Use of Parametric and In-Context Knowledge in Language Models

arXiv:2510.02370v3 Announce Type: replace Abstract: Large language models leverage both parametric knowledge acquired during pretraining and in-context knowledge provided at inference time. Crucially,

Integrating Feature Selection and Machine Learning for Nitrogen Assessment in Grapevine Leaves using In-Field Hyperspectral Imaging

arXiv:2507.17869v3 Announce Type: replace-cross Abstract: Nitrogen (N) is one of the most critical nutrients in winegrape production, influencing vine vigor, fruit composition, and wine quality. Becau

LAGS: Low-Altitude Gaussian Splatting with Groupwise Heterogeneous Graph Learning

arXiv:2604.16910v1 Announce Type: new Abstract: Low-altitude Gaussian splatting (LAGS) facilitates 3D scene reconstruction by aggregating aerial images from distributed drones. However, as LAGS priori

LiveGraph: Active-Structure Neural Re-ranking for Exercise Recommendation

arXiv:2602.17036v2 Announce Type: replace-cross Abstract: The continuous expansion of digital learning environments has catalyzed the demand for intelligent systems capable of providing personalized e

Local learning for stable backpropagation-free neural network training towards physical learning

arXiv:2603.24790v2 Announce Type: replace Abstract: While backpropagation and automatic differentiation have driven deep learning's success, the physical limits of chip manufacturing and rising enviro

MambaKick: Early Penalty Direction Prediction from HAR Embeddings

arXiv:2604.16588v1 Announce Type: new Abstract: Penalty kicks in soccer are decided under extreme time constraints, where goalkeepers benefit from anticipating shot direction from the kickers motion b

Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance

arXiv:2604.17650v1 Announce Type: new Abstract: LLMs are increasingly deployed in dynamic, real-world settings, where the distribution of user prompts can shift substantially over time as new tasks, p

Research

Modeling, Control and Self-sensing of Dielectric Elastomer Soft Actuators: A Review

arXiv:2604.17199v1 Announce Type: new Abstract: Dielectric elastomer actuators (DEAs) have garnered extensive attention especially in soft robotic applications over the past few decades owing to the a

researcharxiv-cs-ro

Modeling Human Perspectives with Socio-Demographic Representations

arXiv:2604.18069v1 Announce Type: new Abstract: Humans often hold different perspectives on the same issues. In many NLP tasks, annotation disagreement can reflect valid subjective perspectives. Model

MoGERNN: An Inductive Traffic Predictor for Unobserved Locations

arXiv:2501.12281v2 Announce Type: replace Abstract: Given a partially observed road network, how can we predict the traffic state of interested unobserved locations? Traffic prediction is crucial for

MoVE: Translating Laughter and Tears via Mixture of Vocalization Experts in Speech-to-Speech Translation

arXiv:2604.17435v1 Announce Type: new Abstract: Recent Speech-to-Speech Translation (S2ST) systems achieve strong semantic accuracy yet consistently strip away non-verbal vocalizations (NVs), such as

MU-GeNeRF: Multi-view Uncertainty-guided Generalizable Neural Radiance Fields for Distractor-aware Scene

arXiv:2604.17965v1 Announce Type: new Abstract: Generalizable Neural Radiance Fields (GeNeRFs) enable high-quality scene reconstruction from sparse views and can generalize to unseen scenes. However,

NaviFormer: A Deep Reinforcement Learning Transformer-like Model to Holistically Solve the Navigation Problem

arXiv:2604.16967v1 Announce Type: new Abstract: Path planning is usually solved by addressing either the (high-level) route planning problem (waypoint sequencing to achieve the final goal) or the (low

Neighbor Embedding for High-Dimensional Sparse Poisson Data

arXiv:2604.16932v1 Announce Type: cross Abstract: Across many scientific fields, measurements often represent the number of times an event occurs. For example, a document can be represented by word oc

NOOUGAT: Towards Unified Online and Offline Multi-Object Tracking

arXiv:2509.02111v2 Announce Type: replace Abstract: The long-standing division between extit{online} and extit{offline} Multi-Object Tracking (MOT) has led to fragmented solutions that fail to address

OFlow: Injecting Object-Aware Temporal Flow Matching for Robust Robotic Manipulation

arXiv:2604.17876v1 Announce Type: new Abstract: Robust robotic manipulation requires not only predicting how the scene evolves over time, but also recognizing task-relevant objects in complex scenes.

Omni-Embed-Audio: Leveraging Multimodal LLMs for Robust Audio-Text Retrieval

arXiv:2604.18360v1 Announce Type: cross Abstract: Audio-text retrieval systems based on Contrastive Language-Audio Pretraining (CLAP) achieve strong performance on traditional benchmarks; however, the

PlankFormer: Robust Plankton Instance Segmentation via MAE-Pretrained Vision Transformers and Pseudo Community Image Generation

arXiv:2604.17856v1 Announce Type: new Abstract: Plankton monitoring is essential for assessing aquatic ecosystems but is limited by the labor-intensive nature of manual microscopic analysis. Automatin

Preventing overfitting in deep learning using differential privacy

arXiv:2604.16334v1 Announce Type: new Abstract: The use of Deep Neural Network based systems in the real world is growing. They have achieved state-of-the-art performance on many image, speech and tex

Putting a Face to Forgetting: Continual Learning meets Mechanistic Interpretability

arXiv:2601.22012v2 Announce Type: replace Abstract: Catastrophic forgetting in continual learning is often measured at the performance or last-layer representation level, overlooking the underlying me

RAG-DIVE: A Dynamic Approach for Multi-Turn Dialogue Evaluation in Retrieval-Augmented Generation

arXiv:2604.16310v1 Announce Type: cross Abstract: Evaluating Retrieval-Augmented Generation (RAG) systems using static multi-turn datasets fails to capture the dynamic nature of real-world dialogues.

Ranking Abuse via Strategic Pairwise Data Perturbations

arXiv:2604.17805v1 Announce Type: new Abstract: Pairwise ranking systems based on Maximum Likelihood Estimation (MLE), such as the Bradley-Terry model, are widely used to aggregate preferences from pa

RASP-Tuner: Retrieval-Augmented Soft Prompts for Context-Aware Black-Box Optimization in Non-Stationary Environments

arXiv:2604.18026v1 Announce Type: new Abstract: Many deployed systems expose black-box objectives whose minimizing configuration shifts with an externally observed context. When contexts revisit a sma

ReconVLA: An Uncertainty-Guided and Failure-Aware Vision-Language-Action Framework for Robotic Control

arXiv:2604.16677v1 Announce Type: new Abstract: Vision-language-action (VLA) models have emerged as generalist robotic controllers capable of mapping visual observations and natural language instructi

REFLEX: Reference-Free Evaluation of Log Summarization via Large Language Model Judgment

arXiv:2511.07458v2 Announce Type: replace Abstract: Evaluating log summarization systems is challenging due to the lack of high-quality reference summaries and the limitations of existing metrics like

Agents

Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understanding

arXiv:2510.15253v3 Announce Type: replace Abstract: Document understanding is critical for applications from financial analysis to scientific discovery. Current approaches, whether OCR-based pipelines

agentsarxiv-cs-cl

Shifting the Gradient: Understanding How Defensive Training Methods Protect Language Model Integrity

arXiv:2604.16423v1 Announce Type: new Abstract: Defensive training methods such as positive preventative steering (PPS) and inoculation prompting (IP) offer surprising results through seemingly simila

SIGMA: A Semantic-Grounded Instruction-Driven Generative Multi-Task Recommender at AliExpress

arXiv:2602.22913v2 Announce Type: replace-cross Abstract: With the rapid evolution of Large Language Models (LLMs), generative recommendation is gradually reshaping the paradigm of recommender systems

SpaceDex: Generalizable Dexterous Grasping in Tiered Workspaces

arXiv:2604.17888v1 Announce Type: new Abstract: Generalizable grasping with high-degree-of-freedom (DoF) dexterous hands remains challenging in tiered workspaces, where occlusion, narrow clearances, a

SPaRSe-TIME: Saliency-Projected Low-Rank Temporal Modeling for Efficient and Interpretable Time Series Prediction

arXiv:2604.17350v1 Announce Type: cross Abstract: Time series forecasting is traditionally dominated by sequence-based architectures such as recurrent neural networks and attention mechanisms, which p

Still Between Us? Evaluating and Improving Voice Assistant Robustness to Third-Party Interruptions

arXiv:2604.17358v1 Announce Type: new Abstract: While recent Spoken Language Models (SLMs) have been actively deployed in real-world scenarios, they lack the capability to discern Third-Party Interrup

STRIKE: Additive Feature-Group-Aware Stacking Framework for Credit Default Prediction

arXiv:2604.17622v1 Announce Type: new Abstract: Credit risk default prediction remains a cornerstone of risk management in the financial industry. The task involves estimating the likelihood that a bo

Surgical Repair of Insecure Code Generation in LLMs

arXiv:2604.16697v1 Announce Type: cross Abstract: Large language models write production code, and yet they routinely introduce well-known vulnerabilities. We show that this is not a knowledge deficit

TensorHub: Rethinking AI Model Hub with Tensor-Centric Compression

arXiv:2604.17104v1 Announce Type: cross Abstract: Modern AI models are growing rapidly in size and redundancy, leading to significant storage and distribution challenges in model hubs. We present Tens

The Role of Vocabularies in Learning Sparse Representations for Ranking

arXiv:2509.16621v2 Announce Type: replace-cross Abstract: Learned Sparse Retrieval (LSR) such as SPLADE has growing interest for effective semantic 1st stage matching while enjoying the efficiency of

TokenChain: A Discrete Speech Chain via Semantic Token Modeling

arXiv:2510.06201v1 Announce Type: cross Abstract: Machine Speech Chain, simulating the human perception-production loop, proves effective in jointly improving ASR and TTS. We propose TokenChain, a ful

Towards Intelligent Legal Document Analysis: CNN-Driven Classification of Case Law Texts

arXiv:2604.17674v1 Announce Type: new Abstract: Legal practitioners and judicial institutions face an ever-growing volume of case-law documents characterised by formalised language, lengthy sentence s

Tree of Concepts: Interpretable Continual Learners in Non-Stationary Clinical Domains

arXiv:2604.17089v1 Announce Type: new Abstract: Continual learning aims to update models under distribution shift without forgetting, yet many high-stakes deployments, such as healthcare, also require

Trustworthy deep domain adaptation for wearable photoplethysmography signal analysis with decision-theoretic uncertainty quantification

arXiv:2604.17480v1 Announce Type: new Abstract: In principle, deep generative models can be used to perform domain adaptation; i.e. align the input feature representations of test data with that of a

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning

arXiv:2507.21545v3 Announce Type: replace Abstract: Robotic task planning in real-world environments requires reasoning over implicit constraints from language and vision. While LLMs and VLMs offer st