Search: “applications”

Stability Enhanced Gaussian Process Variational Autoencoders

arXiv:2604.09331v1 Announce Type: new Abstract: A novel stability-enhanced Gaussian process variational autoencoder (SEGP-VAE) is proposed for indirectly training a low-dimensional linear time invaria

13 Apr 2026

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Applications

SynDocDis: A Metadata-Driven Framework for Generating Synthetic Physician Discussions Using Large Language Models

DGX agent

arXiv:2604.08555v1 Announce Type: new Abstract: Physician-physician discussions of patient cases represent a rich source of clinical knowledge and reasoning that could feed AI agents to enrich and eve

applicationsarxiv-cs-cl

13 Apr 2026

A Comparative Study of Demonstration Selection for Practical Large Language Models-based Next POI Prediction

arXiv:2604.06207v1 Announce Type: cross Abstract: This paper investigates demonstration selection strategies for predicting a user's next point-of-interest (POI) using large language models (LLMs), ai

CompoDistill: Attention Distillation for Compositional Reasoning in Multimodal LLMs

arXiv:2510.12184v2 Announce Type: replace Abstract: Recently, efficient Multimodal Large Language Models (MLLMs) have gained significant attention as a solution to their high computational complexity,

Learning Geometry-Aware Nonprehensile Pushing and Pulling with Dexterous Hands

arXiv:2509.18455v4 Announce Type: replace Abstract: Nonprehensile manipulation, such as pushing and pulling, enables robots to move, align, or reposition objects that may be difficult to grasp due to

Production-Ready Automated ECU Calibration using Residual Reinforcement Learning

arXiv:2604.07059v1 Announce Type: new Abstract: Electronic Control Units (ECUs) have played a pivotal role in transforming motorcars of yore into the modern vehicles we see on our roads today. They ac

State and Trajectory Estimation of Tensegrity Robots via Factor Graphs and Chebyshev Polynomials

arXiv:2604.08185v1 Announce Type: new Abstract: Tensegrity robots offer compliance and adaptability, but their nonlinear, and underconstrained dynamics make state estimation challenging. Reliable cont

Affordance-Aware Interactive Decision-Making and Execution for Ambiguous Instructions

arXiv:2602.05273v2 Announce Type: replace Abstract: Enabling robots to explore and act in unfamiliar environments under ambiguous human instructions by interactively identifying task-relevant objects

Backward Compatibility in Zero-Bit Neural Audio Watermarking

arXiv:2610.22296v1 Announce Type: cross Abstract: Neural watermarking systems are typically trained as tightly coupled embedder-detector pairs and implicitly assume static deployment. In real-world de

BOLT: Universal Classifier Training via a Bayes-Error Upper Bound

arXiv:2501.07754v2 Announce Type: replace-cross Abstract: This work introduces a novel approach to compute a universal upper bound on the Bayes error rate (BER) from classifier-output samples, which s

CF-AVSS: A Coarse-to-Fine Audio-Visual Speech Separation Framework with Target-Speaker Refinement and Post-Fusion for Real-World AVSE Challenge

arXiv:2610.21773v1 Announce Type: cross Abstract: Audio-visual speech enhancement (AVSE) leverages visual cues to recover target speech from mixtures corrupted by reverberation, noise, and overlapping

CoCopula: Conformal Calibration and Copula Aggregation for Reliable Renewable Energy Forecasting

arXiv:2602.02583v2 Announce Type: replace Abstract: The rapid growth of renewable energy penetration has intensified the need for reliable probabilistic forecasts to support grid operations at aggrega

Do Emergent Misalignment Models Share a Circuit?

arXiv:2610.20887v1 Announce Type: new Abstract: Fine-tuning language models on narrowly defined harmful tasks can induce emergent misalignment (EM) across unrelated domains. While prior work has ident

Documenting Trofinetide Treatment Phenotypes in Rett Syndrome with a Dual-LLM Consensus Pipeline

arXiv:2610.22062v1 Announce Type: cross Abstract: Objective: Trofinetide, approved in 2023 as the first Rett syndrome treatment, lacks scalable real-world monitoring because chart review is labor-inte

applicationsarxiv-cs-cl

EgoJEPA: Beyond Retargeting for Dexterous Manipulation from Egocentric Videos

arXiv:2610.20904v1 Announce Type: cross Abstract: Egocentric human videos offer a scalable alternative to costly robot demonstra- tions, yet transferring their manipulation priors to robot control rem

FilterFusion: Prior-Guided Adaptive Filter Fusion for Efficient Video Denoising

arXiv:2610.21505v1 Announce Type: new Abstract: Real-world video denoising for communication systems must handle mixed degradations such as sensor noise, compression artifacts, and motion-induced inco

Graph Dirichlet Energy for Fitting-Free Bivariate Causal Inference

arXiv:2610.21892v1 Announce Type: new Abstract: We propose the Graph Dirichlet Energy Causal Inference (GDECI) criterion for distinguishing cause from effect in bivariate settings. For a candidate dir

IDfRA: Self-Verification for Iterative Design in Robotic Assembly

arXiv:2509.16998v2 Announce Type: replace Abstract: Design for Robotic Assembly (DfRA) remains largely dependent on manual planning and heuristic simulation, limiting scalability and robustness in com

In-Context Preference-Conditioned Pareto Set Learning from Limited Offline Data

arXiv:2610.21736v1 Announce Type: new Abstract: Multi-objective optimization involves diverse preferences over conflicting objectives. Rather than returning a finite set of trade-off solutions, prefer

Learning and Forecasting Multiscale Spatiotemporal Epidemic Dynamics with Lagrangian-Eulerian Graph Neural ODEs

arXiv:2610.21223v1 Announce Type: new Abstract: Accurate medium- to long-range epidemic forecasting requires extrapolating high-dimensional, heterogeneous and nonstationary dynamics from partial obser

LTM: Latent Transition Based In-Context Memory for Vision-Language-Action Models

arXiv:2610.21362v1 Announce Type: cross Abstract: Robotic manipulation often requires remembering interactions that are no longer visible. We introduce Latent Transition Memory (LTM), which stores his

Money-Mule Detection as a Relational Learning Problem: A Study on the RBIH NFPC Dataset

arXiv:2610.21314v1 Announce Type: new Abstract: Money-mule networks move criminal funds through many small transfers, each of which looks ordinary on its own. What marks an account as a mule lies outs

Ontology Refinement with Embeddings and LLMs: A Case Study on CASTON

arXiv:2610.21466v1 Announce Type: new Abstract: Ontologies are widely used to represent and organize complex knowledge in domains such as biomedicine and healthcare. However, constructing reliable ont

QREF: Improving DeepSearch Agents by Aligning Search with Reasoning via Query Refinement and Evidence Filtering

arXiv:2610.21512v1 Announce Type: new Abstract: DeepSearch agents achieve strong performance on complex information-seeking tasks through iterative search and reasoning. However, they often issue inte

Model Releases

Qwen-Audio-Jev: A Unified Interface for Audio Decisions

model-releasesarxiv-cs-ai

arXiv:2610.21614v1 Announce Type: cross Abstract: Large audio language models (LALMs) have made substantial progress in audio understanding. However, in high-throughput applications requiring frequent

SCRIBE: Scalable Contextual Representations of Interpretable Brain-Grounded Semantics

arXiv:2610.21518v1 Announce Type: new Abstract: Understanding how the human brain constructs meaning from real-world language remains a fundamental challenge, as semantics depend on context that varie

Self-Refining Vision Language Model for Robotic Failure Detection and Reasoning

arXiv:2602.12405v2 Announce Type: replace-cross Abstract: Reasoning about failures is crucial for building reliable and trustworthy robotic systems. Prior approaches either treat failure reasoning as

Sign Betting for Misspecified Regression: Variance Adaptivity and Optimal Approximation

arXiv:2610.20903v1 Announce Type: new Abstract: We study bounded regression under model misspecification, evaluating a function f by its L_1(P_X) distance to the conditional mean eta(x)=E[Ymid X=x], r

T2-z: Test-Time Optimization of Environment Latents for Robotic World Models

arXiv:2610.22364v1 Announce Type: cross Abstract: Predicting how the world responds to an action requires more than what can be seen: robots must account for environmental factors that are neither dir

Task-Centric Multimodal Learning for Cognitive Impairment Detection

arXiv:2610.20906v1 Announce Type: cross Abstract: Dementia affects millions of older adults worldwide, yet early detection remains difficult outside clinical settings. Traditional models primarily rel

applicationsarxiv-cs-cl

Teaching DINOv3 About Partial 3D Geometry: A Self-Supervised Geometry-Aware Approach

arXiv:2610.21802v1 Announce Type: new Abstract: Partial shape matching is a crucial yet underexplored problem in 3D vision, with significant relevance to real-world scenarios where shapes are often on

TGrasp6D: Task-Informed Vision-Language Priors and Pose Refinement enable Zero-Shot Task-Oriented 6DoF Grasping

arXiv:2610.20901v1 Announce Type: cross Abstract: Task-Oriented Grasping (TOG) has emerged as an important skill for purposeful robotic manipulation. Given the task of using a knife to 'slice bread,'

Tourist arrival forecasting with game-theoretic social influence weighting and deep learning

arXiv:2507.03411v2 Announce Type: replace Abstract: In the era of Industry 5.0, data-driven decision-making has become indispensable for planning in service systems such as tourism. This paper propose

Trajectory-based Diffusion from One-shot Human Video for Generalizable Manipulation

arXiv:2610.21792v1 Announce Type: new Abstract: Imitation learning enables robots to perform complex tasks by leveraging human-collected demonstrations. However, most existing approaches require labor

A Graph-Based Analysis of Comparability, Scale, and Attribution in Private Transformer Inference

arXiv:2610.19607v1 Announce Type: cross Abstract: Rising privacy concerns around large language models have accelerated research in private Transformer inference (PTI). Synthesizing the empirical clai

A large-scale pipeline for LLM-assisted corpus annotation: variation and change in the English consider construction

arXiv:2510.12306v4 Announce Type: replace Abstract: As natural language corpora expand at an unprecedented rate, manual annotation remains a significant methodological bottleneck in corpus linguistic

applicationsarxiv-cs-cl

Agronomic Characterization and Time-Series UAV Phenotyping to Support Field Pea Breeding in Iowa

arXiv:2610.19154v1 Announce Type: new Abstract: Field pea has gained interest in the Midwest U.S. and has the potential to benefit Iowa cropping systems. This study evaluated 17 accessions and 7 Canad

An Initial Study of Physiological Markers for Deepfake Speech Detection

arXiv:2610.18934v1 Announce Type: cross Abstract: Conventional deepfake speech detectors primarily target synthesis artifacts and often degrade under unseen attacks or recording conditions. Human spee

AutoRSR: Automated Real-to-Sim-to-Real Data Generation for Scalable Robot Learning

arXiv:2610.20336v1 Announce Type: new Abstract: Scaling embodied robot learning requires large and diverse manipulation datasets, but collecting real-world demonstrations remains expensive in human ef

Chain of Time: In-Context Physical Simulation with Image Generation Models

arXiv:2511.00110v2 Announce Type: replace Abstract: We propose a novel cognitively-inspired prompting method to stabilize and interpret the physical simulation produced by autoregressive image generat

Cognifying Education: Mapping AI's transformative role in emotional, creative, and collaborative learning

arXiv:2509.25266v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is rapidly reshaping educational practice, challenging long held assumptions about teaching and learning. This ar

Complementary Future Token Pruning for World Action Models

arXiv:2610.19957v1 Announce Type: new Abstract: World action models (WAMs) jointly predict future visual states and robot actions, but processing dense future-frame tokens incurs substantial inference

Model Releases

Confidently Wrong: Detecting Hallucinations in Financial Question Answering from LLM Internal States

model-releasesarxiv-cs-cl

arXiv:2607.11414v2 Announce Type: replace Abstract: Large language models (LLMs) in financial applications fail most consequentially when they are confidently wrong. Hedged, uncertain answers invite s

Contact-UAN: Unsupervised Actuator Networks as a Residual World Model for Humanoid Control

arXiv:2610.18991v1 Announce Type: new Abstract: Humanoid policies trained in simulation can transfer qualitatively to hardware while failing to transfer the force interactions learned during training,

Coordi-pi: Coordination-Aware Dual-Hand Action Representation for Bimanual Dexterous Manipulation

arXiv:2610.19753v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong potential for general-purpose robotic manipulation, but extending them to bimanual dexterous manip

Research

Design and Characterization of a Unified Continuum Robot Actuation Platform

arXiv:2610.19798v1 Announce Type: new Abstract: Continuum robots enable dexterous access to confined spaces in applications such as minimally invasive surgery and industrial inspection. However, their

researcharxiv-cs-ro

Few-Shot Adaptation for Anomalous Sound Detection at Low False-Positive Rate

arXiv:2610.19893v1 Announce Type: cross Abstract: Reliable fault detection is crucial for industrial machinery in large-scale facilities, where unexpected failures can cause costly downtime and produc

FleetPilot: Fine-Grained Steering Empowers Real-World LLM Personalization

arXiv:2610.14970v1 Announce Type: new Abstract: With the rapid evolution of large language models (LLMs), there is an increasing demand for effective personalization techniques that can adapt model be