Search: “applications”

Trajectory-Derived Confidence for Reliable, Resource-Aware Clinical Text-to-SQL Agents

model-releasesarxiv-cs-lg

arXiv:2610.04156v1 Announce Type: cross Abstract: LLM agents for clinical text-to-SQL applications reason autonomously over multiple steps but cannot assess whether their own reasoning or outputs can

6 Oct 2026

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Applications

Video Replanning via Latent Embedding Refinement and Rejection-Based Sampling

DGX agent

arXiv:2510.17315v3 Announce Type: replace Abstract: Video planning has emerged as a flexible framework for robot manipulation, in which a generative model predicts a video of task completion, and a do

applicationsarxiv-cs-ro

6 Oct 2026

When and What to Prune? Stage-Aware Visual Token Pruning for Efficient VLA

arXiv:2610.05273v1 Announce Type: new Abstract: Visual token pruning is an effective way to accelerate vision-language models and is especially useful for vision-language-action (VLA) inference, where

6 Oct 2026

16-bit Precision of Convolutional Neural Networks on Microcontroller Units for 8-bit Costs

arXiv:2610.03402v1 Announce Type: new Abstract: To deploy deep neural networks on edge hardware, highly efficient inference schemes are necessary that retain high accuracy. This work presents W16A16,

AGT-CV: An Aerial-Ground Team Cross-View Dataset for Heterogeneous Robot Teams in Unstructured Environments

arXiv:2605.06478v2 Announce Type: replace Abstract: Heterogeneous air-ground robot teams combine complementary sensing modalities, mobility characteristics, and spatial viewpoints that can significant

Becoming Suspicious Across Borders: Algorithmic Extraterritoriality and AI-Driven Financial Surveillance

arXiv:2610.03425v1 Announce Type: new Abstract: Suspicion is an important, yet elusive concept in anti-money laundering and counter-terrorist financing (AML/CFT), which allows for intervention below t

BioMol-MQA: A Multi-Modal Question Answering Dataset For LLM Reasoning Over Bio-Molecular Interactions

arXiv:2506.05766v2 Announce Type: replace Abstract: Retrieval augmented generation (RAG) has shown great power in improving Large Language Models (LLMs). However, most existing RAG-based LLMs are dedi

applicationsarxiv-cs-cl

Building Interpretable Feature Representations for Resume-Vacancy Matching by Distilling Production LLM Signals

arXiv:2610.03112v1 Announce Type: new Abstract: Matching candidates to vacancies is central to recruitment, and a recruiter needs to see why a candidate fits, not only a single opaque relevance score.

applicationsarxiv-cs-cl

Capturing Dynamics: The 4D Facial Expression Intensity Dataset

arXiv:2610.02647v1 Announce Type: new Abstract: The estimation and analysis of facial expression intensity play a crucial role in affective communication and human-computer interaction. Previous resea

Certified Mechanistic Edits: Behavioral Guarantees for Skill Removal and Preservation

arXiv:2610.03502v1 Announce Type: cross Abstract: Mechanistic edits (ablations, weight edits, activation steering) are the standard tools for unlearning a harmful capability from a neural network whil

Compound AI System Reliability: A Failure Taxonomy and Resilience Pattern Catalog from 150 Production Incidents

arXiv:2610.02503v1 Announce Type: cross Abstract: Deploying compound AI systems reliably and safely requires understanding failure modes that emerge at component boundaries, not within individual mode

Conformal Prediction for Time Series with Deep Sequence Models

arXiv:2610.02357v1 Announce Type: cross Abstract: Recent advances in deep learning for time series prediction have amplified the need for reliable uncertainty quantification. Conformal prediction has

Decoupling Memory from Context: Structured Memory for Token-Efficient Test-Time Continual Learning

model-releasesarxiv-cs-ai

arXiv:2610.02687v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in enterprise, scientific, and medical applications, where agents must incorporate domain-specifi

Diffusion-Based Synthetic Data Pretraining for Enhancing Activity Recognition

arXiv:2610.02292v1 Announce Type: cross Abstract: Human activity recognition (HAR) is increasingly important for healthcare, well-being, and daily monitoring ap- plications, for which detecting alimen

Dual-Context Analog Retrieval for Time Series Forecasting

arXiv:2610.03491v1 Announce Type: new Abstract: Most long-term time-series forecasting models map the look-back window directly to the full horizon in a single pass. While efficient, this design does

Safety

Heads, Tails, and AI Fails: LLMs, Randomness, and Human Judgments

arXiv:2406.00092v2 Announce Type: replace Abstract: Randomness is central to human cognition and to many applications in which large language models are deployed, yet probabilistic token generation do

safetyarxiv-cs-ai

High-Dimensional Asymptotics and Dataset Selection for Private Transfer Learning

arXiv:2610.02578v1 Announce Type: cross Abstract: To commit to buying external data or participate in collaborative learning, one must decide whether the additional data will improve prediction enough

Jumping the Line: Exploiting Length Predictions in LLM Scheduling

arXiv:2610.03430v1 Announce Type: new Abstract: Efficient request scheduling is increasingly important for reducing completion time in large language model (LLM) serving. Size-based policies such as S

Learning Query Encoders Can Be Hard Even When Vector Retrieval Is Geometrically Easy

arXiv:2610.02749v1 Announce Type: cross Abstract: Efficient vector retrieval requires both a corpus geometry that supports retrieving the right documents through vector similarity, and a query encoder

Learning to Assess Heartbeat Observability for mmWave Heart-Rate Sensing

arXiv:2610.03570v1 Announce Type: new Abstract: Contactless heart-rate sensing with millimeter-wave (mmWave) radar requires assessing whether individual measurements support reliable estimation. We st

LOCUS: Landmark-Oriented Container Discrimination Using Spatial Graphs

arXiv:2610.02803v1 Announce Type: new Abstract: As robots are increasingly deployed in unstructured, real-world environments, the ability to reason about complex spatial and semantic relationships amo

Mapping and Advancing the Scalability-Accuracy Frontier of Nonlinear Causal Discovery

arXiv:2610.03258v1 Announce Type: cross Abstract: Scalable nonlinear causal discovery requires methods that combine flexible mechanism estimators with efficient search over large graph spaces. Several

MoSE3: Learning World-Space SE(3) at Every Pixel

arXiv:2610.03716v1 Announce Type: new Abstract: Dense 3D point tracking has been a prominent paradigm for modeling motion in dynamic scenes, but a point track is just a 3-DoF translation curve per pix

Most-Recent Anchoring with Recurrent Ordering for Time Series Forecasting

arXiv:2610.03494v1 Announce Type: new Abstract: Long-term forecasting models commonly process all patches in a look-back window using the same fixed stack. Older contextual patches and recent evidence

Predictor-Guided Latent Space Codon Optimization for Maximizing Protein Expression

arXiv:2610.03098v1 Announce Type: new Abstract: Codon optimization, the process of selecting synonymous codons to improve mRNA translation efficiency and protein expression, is central to therapeutic

Proprioceptive Sketches as Long-Horizon Intent for Generative Action Policies

arXiv:2610.02759v1 Announce Type: new Abstract: Generative robot policies predict short action chunks but lack explicit long-horizon intent. Recent methods expose longer-horizon structure through lang

RATE: Risk-Aware Tactile Encoding for Contact-rich Robotic Manipulation

arXiv:2610.03538v1 Announce Type: new Abstract: Tactile sensing is particularly valuable for contact-rich robotic manipulation. Recent work has made substantial progress in tactile representation lear

Reasoning with Evidence, Not Merely Rationales: Verifiable Preference Proofs for LLM-Based Recommendation

arXiv:2610.02968v1 Announce Type: new Abstract: Large language models (LLMs) can infer user preferences from interaction histories and reviews, yet the rationales they generate may not reflect the inf

ReSCUE: Re-translation with Sentence Commitment for Unsegmented Long-Form Simultaneous Sign Language Translation

arXiv:2610.03022v1 Announce Type: cross Abstract: Simultaneous Sign Language Translation (SLT) is critical for real-time communication, yet existing methods remain largely confined to sentence-level,

applicationsarxiv-cs-cl

RIFAR: Reliability and Forgetting-Aware Replay for Continual Robot Learning

arXiv:2610.03079v1 Announce Type: new Abstract: Genuine embodied agency requires robots to turn continuous real-world experience into lasting, transferable skills. This demands continual learning that

ROVE: Unlocking Human Interventions for Humanoid Manipulation via Reinforcement Learning

arXiv:2606.17011v2 Announce Type: replace-cross Abstract: Human interventions provide crucial corrective signals for post-training Vision-Language-Action (VLA) models. However, enabling seamless human

SCION: Scene Composition with Instanced Neural Primitives

arXiv:2610.02322v1 Announce Type: new Abstract: Real-world scenes are compositional: bricks, blades of grass, pebbles, and tree leaves recur across human-built and natural environments. Existing neura

The Price of Greenwashing: Algorithmic Verification and Market Discipline using Conformal Machine Learning

arXiv:2610.02225v1 Announce Type: new Abstract: While corporate sustainability mandates are expanding, the systemic reliance on self-reported emissions data exposes financial markets to pervasive gree

Time Series Forecasting Benchmarks Need Scenario-Grounded Stress Testing

arXiv:2610.02608v1 Announce Type: new Abstract: Time series forecasting (TSF) increasingly drives decisions in transportation, energy, finance, healthcare, and infrastructure, yet current evaluation r

Uncertainty Quantification for Flow-Based Generalist Robot Policies

arXiv:2606.18043v2 Announce Type: replace-cross Abstract: Generalist robot policies, such as vision-language-action models (VLAs) and world-action models (WAMs), combine powerful pretrained backbones

3DROID: A Renderable 3D Gaussian Dataset with Measured Per-Scene Reliability

arXiv:2610.01744v1 Announce Type: new Abstract: Robot manipulation models primarily reason from 2D observations while acting in the 3D physical world. To bridge this gap, recent work has augmented rob

4Director: Controlling Video World Models with Rigid 3D Geometry

arXiv:2610.02160v1 Announce Type: new Abstract: Precise control over camera and object motion is essential for professional video production. Existing methods control objects only coarsely, through im

A First Glance at Jev for Network Traffic Classification: Accuracy, Processing Time, and Cost

model-releasesarxiv-cs-lg

arXiv:2610.00376v1 Announce Type: new Abstract: We evaluate Jev on ten dataset-defined application labels in CESNET-QUICEXT-25 using only the first ten packets' sizes, directions, and inter-packet tim

A Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders

arXiv:2610.01949v1 Announce Type: cross Abstract: Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are t

BLT*: Informed Belief Localization Trees for Uncertainty-Aware Planning on Digital Twins

arXiv:2610.01972v1 Announce Type: new Abstract: We present Informed Belief Localization Trees* (Informed BLT*), a sampling-based belief space planning (BSP) algorithm that scales to large outdoor digi

Causal-Aware Tabular GANs with Reinforcement Learning

arXiv:2510.24046v2 Announce Type: replace-cross Abstract: Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlook

ChunkVLA-AM: Parallel Action Chunking for Vision-Language-Action Robot Control in Additive Manufacturing

arXiv:2610.01856v1 Announce Type: new Abstract: Vision-language-action (VLA) models unify visual perception, language understanding, and action generation, offering new opportunities for automation in

Continual Learning for 6-DoF Grasp Synthesis via Experience and Demonstrations

arXiv:2610.01301v1 Announce Type: cross Abstract: Most current grasp synthesis systems are trained offline and remain fixed during deployment. While this works well when deployment conditions resemble

DecomVoxel: Harnessing 3D-Native Priors with Guided In-situ Denoising Optimization for Decompositional Scene Reconstruction

arXiv:2610.01914v1 Announce Type: new Abstract: Decompositional scene reconstruction aims to reconstruct high-quality objects and background, yet existing methods still struggle with the level of qual

Deep Symmetric Autoencoders from the Eckart-Young-Schmidt Perspective

model-releasesarxiv-cs-lg

arXiv:2506.11641v2 Announce Type: replace-cross Abstract: Deep autoencoders have become a fundamental tool in various machine learning applications, ranging from dimensionality reduction and reduced o

Evaluating LLM-Generated Preference Distributions

arXiv:2610.01000v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as probabilistic generators for simulation, synthetic data generation, and decision support in settin

EvenSplat: Coupled 2D-3D Decomposition for Gaussian Splatting under Exposure and Illumination Variation

arXiv:2610.01876v1 Announce Type: new Abstract: A surface photographed under even light presents nearly the same appearance from every angle; the same surface under uneven light does not. Exposure cha

Exposing the Cost of Deep Learning Audio Development

arXiv:2610.01619v1 Announce Type: cross Abstract: The environmental impact of deep learning has attracted increasing attention over the past decade. Existing studies mainly focus on the energy and car