Search: “papers”

REQAP: Resilient Weight Packing and Quantization for Edge DNN Acceleration

arXiv:2609.17555v1 Announce Type: cross Abstract: Efficient deployment of Deep Neural Networks (DNNs) on edge accelerators requires aggressive model compression while maintaining reliability in fault-

researcharxiv-cs-ai

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Revisiting Distributed Sign-Based Variance Reduction

DGX agent

arXiv:2609.18656v1 Announce Type: new Abstract: Sign-based methods reduce communication costs in distributed environments, but aggregating local signs can introduce bias when data are heterogeneous. A

safetyarxiv-cs-lg

17 Sept 2026

rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference

arXiv:2609.19104v1 Announce Type: cross Abstract: Factory work is a promising early scenario for embodied AI: assigning repetitive manual jobs to robots has clear economic payoff, and a structured sta

safetyarxiv-cs-ai

Selective Prediction and Uncertainty-Aware Referral for Pap Smear Classification

arXiv:2609.17545v1 Announce Type: new Abstract: Deep learning models for cervical cytology are almost always evaluated as if every prediction must be acted upon, yet a screening system deployed alongs

researcharxiv-cs-cv

Semantic-ITC: A Frame-wise Indoor Mobile Laser Scanning Dataset and Benchmark for Semantic Segmentation

arXiv:2609.18493v1 Announce Type: new Abstract: Semantic labels for indoor mobile laser scanning (MLS) frames remain largely absent from current point cloud semantic segmentation benchmarks, which mai

Simultaneous Arrival Control for Distributed Multi-Robot Systems with Curvature and Constant-Speed Constraints

arXiv:2607.14781v2 Announce Type: replace Abstract: The simultaneous arrival of multiple mobile robots at a target point is crucial for cooperation tasks such as cooperative encirclement, disaster rel

researcharxiv-cs-ro

Social Laws for Multi-agent Coordination in Stochastic Environments

arXiv:2609.18929v1 Announce Type: cross Abstract: In multi-agent environments, coordinating agents to prevent interference and ensure robust individual performance is a critical challenge. Previous re

safetyarxiv-cs-ai

Stable Filters for Generative Modeling of Graph Signals

arXiv:2609.18759v1 Announce Type: cross Abstract: Generating signals on graphs requires permutation-equivariant models that exhibit stability with respect to relative structural perturbations. While r

Stealthy in Semantics, Antagonistic in Space: Attacking Visible-Infrared Object Detectors via Object-Level Misalignment

arXiv:2609.18133v1 Announce Type: new Abstract: Visible-infrared object detectors are used for robust perception under challenging illumination and weather conditions. Current physical attacks apply c

safetyarxiv-cs-cv

Synthetic Electric Vehicle Charging Session Generation Using a Conditional Variational Autoencoder

arXiv:2609.17808v1 Announce Type: cross Abstract: The increasing adoption of electric vehicles (EVs) is expected to place significant additional demand on residential distribution networks, creating a

applicationsarxiv-cs-lg

The Unbearable Weight: Scaling Models and Methods for UAV Audio Classification

arXiv:2609.17884v1 Announce Type: cross Abstract: As unmanned aerial vehicles (UAVs) become increasingly prevalent in consumer and defense settings, classifying them reliably from limited, modality-sp

Think Before You Move: Latent Motion Reasoning for Text-to-Motion Generation

arXiv:2512.24100v2 Announce Type: replace Abstract: Current state-of-the-art paradigms predominantly treat Text-to-Motion (T2M) generation as a direct translation problem, mapping symbolic language di

safetyarxiv-cs-cv

Token Latency Fairness: Performance Isolation for Multi-Tenant LLM Serving

arXiv:2609.18112v1 Announce Type: cross Abstract: LLM serving is typically offered as a shared, multi-tenant service, where high-demand workloads from one client can cause latency SLO violations for o

safetyarxiv-cs-lg

Toward Composable Network Digital Twins: A Subgraph-Based Latency Prediction Study

arXiv:2609.18704v1 Announce Type: cross Abstract: Modern networks must support changing topologies, configurations, and performance objectives, motivating fast and reliable performance estimation. Net

applicationsarxiv-cs-lg

Toward Markerless Video-based Tremor Analysis: Objective Quantification of Pathological Tremor in Mouse Preclinical Models

arXiv:2609.18753v1 Announce Type: new Abstract: Tremor is a movement disorder characterized by involuntary, rhythmic oscillations of body parts and is a hallmark of several neurological conditions, in

researcharxiv-cs-cv

Uncertainty measurement for complex event prediction in safety-critical systems

arXiv:2411.01289v2 Announce Type: replace Abstract: Complex events originate from other primitive events combined according to defined patterns and rules. Instead of using specialists' manual work to

Unleash LLMs Potential for Sequential Recommendation by Coordinating Dual Dynamic Index Mechanism

arXiv:2409.09253v2 Announce Type: replace-cross Abstract: Owing to the unprecedented capability in semantic understanding and logical reasoning, large language models (LLMs) have shown fantastic poten

safetyarxiv-cs-ai

UWA360CAM: A 360^{irc} 24/7 Real-Time Streaming Camera System for Underwater Applications

arXiv:2309.12668v3 Announce Type: replace Abstract: Omnidirectional camera is a cost-effective and information-rich sensor highly suitable for many marine applications and the ocean scientific communi

researcharxiv-cs-ro

Visual Autoregressive Priors for RAW-to-sRGB Image Signal Processing

arXiv:2609.18302v1 Announce Type: new Abstract: RAW-to-sRGB image signal processing (ISP) must recover perceptually faithful colors and fine details from sensor measurements, often under imperfect spa

Local Ai

WARD: Runtime Workload-Adaptive Vision TRansformer Framework for Dependable Edge AI

arXiv:2609.17556v1 Announce Type: cross Abstract: Edge-deployed AI operate under dynamically changing power budgets, reliability requirements, and input distributions, requiring continuous adaptation.

local-aiarxiv-cs-ai

Which LLM is Best for Translating Natural Language Goals to PDDL

arXiv:2609.18731v1 Announce Type: new Abstract: Bridging the gap between human intent and machine execution remains a challenge in automated planning, where expressing goals in formal languages like P

A unified framework for global and local interpretability using adaptive derivative-ordered random explanation

arXiv:2609.17171v1 Announce Type: cross Abstract: The interpretability of complex machine learning models is of paramount importance, especially in real-world high-stakes domains such as healthcare an

Affect-Prototype Guided Fusion for Open-Vocabulary Incomplete Multi-modal Emotion Recognition

arXiv:2609.16962v1 Announce Type: new Abstract: Open-vocabulary multimodal emotion recognition (OV-MER) aims to generate open natural-language emotion labels from multimodal affective cues. In real-wo

applicationsarxiv-cs-ai

Agents

After the Party: Governing What a Viral Agent-Skill Ecosystem Left Behind

arXiv:2609.17274v1 Announce Type: cross Abstract: AI agents increasingly act through agent skills, i.e., natural-language instructions, that direct a host agent toward shell, network, credential, file

agentsarxiv-cs-ai

Agentic Search Spaces for Tabular Machine Learning

arXiv:2609.16309v1 Announce Type: new Abstract: Despite the rapid progress of LLM-based agents for planning, code generation, and debugging, their practical value for tabular machine learning remains

AquiLLM: Evaluating Faithfulness in Open-Weight RAG-LLM Systems for Scientific Research

arXiv:2609.16519v1 Announce Type: new Abstract: Scientific research increasingly relies on large, heterogeneous data sources, motivating interest in retrieval-augmented generation (RAG) systems that p

AssemblyGrid v1: A Benchmark for Multi-Robot Production with Temporary Coalitions, Local Information, and Geometric Constraints

arXiv:2609.16075v1 Announce Type: cross Abstract: Flexible robotic production requires joint decisions on process progression, material routing, resource assignment, temporary cooperation, and simulta

Tutorials

Attention is All You Need Until You Need Retention

arXiv:2501.09166v2 Announce Type: replace-cross Abstract: Pretrained Transformers keep what they learned in their weights and lose what they observe once a session ends. The first version of this pape

tutorialsarxiv-cs-ai

Beyond Distribution Matching: Semantics-Consistent Tabular Diffusion with Weak Semantic Priors

arXiv:2609.16069v1 Announce Type: cross Abstract: Synthetic tabular data can match real data distributions while still violating the semantic constraints that govern valid tabular rows. This reveals a

applicationsarxiv-cs-ai

Bias Audits Detect Bias but Disagree on Ranking: Evidence from Ten Instruments and Ten Frontier Models

arXiv:2609.15995v1 Announce Type: new Abstract: Emerging AI regulation mandates bias audits of high-risk systems, and audit scores are beginning to be used to rank models. Both uses assume different a

safetyarxiv-cs-cl

Bridging the Perceptual Gap: Residual-Enhanced Downscaling and Manifold-Aware Perception Alignment Adaptation for NR-IQA

arXiv:2609.16664v1 Announce Type: new Abstract: Leveraging Large Vision-Language Models like CLIP has recently set new benchmarks for No-Reference Image Quality Assessment (NR-IQA). However, the contr

CAD-Based Relation Learning and Geometric-Symbolic Planning for Robotic Assembly

arXiv:2609.17263v1 Announce Type: new Abstract: Assembly Sequence Planning (ASP) remains a challenging problem due to its combinatorial nature, making exhaustive planning approaches impractical for co

researcharxiv-cs-ro

Can We Do Interpretable NLI with Graphs Based on Atomic Propositions?

arXiv:2609.16814v1 Announce Type: new Abstract: While Large Language Model (LLM)-based Natural Language Inference (NLI) systems achieve high accuracy, their decision-making processes lack auditable st

Certified Uncertainty Propagation in One-Shot Federated Bayesian Models via Posterior Event Transport

arXiv:2609.16373v1 Announce Type: new Abstract: Probabilistic certification of Bayesian neural networks lower-bounds the posterior probability that a model satisfies a verifier-defined safety property

CLARE: Scalable Class-Incremental Continual Learning via a Sparsity-Based Framework

arXiv:2609.17026v1 Announce Type: cross Abstract: Continual learning must balance the learning of new knowledge with the retention of previously learned knowledge to incrementally learn tasks from a d

CoAdapt: An LLM-based Framework for Adaptive Collaborative Perception in IIoT Robotic Swarms

arXiv:2609.16852v1 Announce Type: new Abstract: Industrial IoT environments increasingly deploy autonomous mobile robots for tasks such as material handling, product assembly, or infrastructure inspec

Collaborative Optimization of Multiclass Imbalanced Learning: Density-Aware and Region-Guided Boosting

arXiv:2512.22478v2 Announce Type: replace Abstract: Numerous studies on Boosting attempt to mitigate classification bias caused by class imbalance. However, existing studies have yet to explore the co

safetyarxiv-cs-lg

Compute-Optimal Pretrain--Fine-tune in Ridge Gradient Descent

arXiv:2609.16262v1 Announce Type: cross Abstract: Pretraining followed by fine-tuning introduces a compute-allocation problem: under a fixed training budget, compute spent improving the upstream objec

Conformal Policy Learning with Distribution-Free Safety Guarantees

arXiv:2609.17296v1 Announce Type: cross Abstract: Policy learning aims to determine who should be treated based on individual characteristics. In high-stakes settings such as medicine and public polic

safetyarxiv-cs-lg

ConGraspXL: Controllable Constraint-Conditioned Dexterous Grasping Motion Synthesis

arXiv:2609.16319v1 Announce Type: cross Abstract: Dexterous grasping is usually conducted for specific tasks, leading to heterogeneous constraints such as specific approach directions, desired contact

researcharxiv-cs-cv

Copula Adapted Directed Acyclic Graph for Cluster Representation of Biomedical Data

arXiv:2609.16240v1 Announce Type: cross Abstract: Diagnostic errors and mislabeling are common in biomedicine, which compromise the reliability of predictive models and data-driven outcomes. Stratifyi

Cross-Domain Inference for Human Localization: Applying Wi-Fi RSSI Data to CSI-Trained Models

arXiv:2609.17204v1 Announce Type: cross Abstract: Wi-Fi signal data can be used to compromise the privacy of individuals. While many existing approaches rely on Channel State Information (CSI), collec

EBL: Efficient Broad Learning for Distributed Adaptive Harmonic Analysis

arXiv:2609.16358v1 Announce Type: cross Abstract: Renewable energy systems and electrified transport have found widespread adoption in recent years. The integration of these non-linear loads, dominate

Agents

End-to-End Latency-Minimizing and Load-Balanced Request Scheduling for Edge LLM Inference in Agentic AI Services

arXiv:2609.17193v1 Announce Type: new Abstract: Large language model (LLM)-powered agentic AI services increasingly demand low-latency inference, motivating the deployment of LLMs across distributed e

agentsarxiv-cs-ai

Tutorials

EventEgoHands++: Event-based Egocentric 3D Hand Mesh Reconstruction with Real Dataset

arXiv:2609.17189v1 Announce Type: new Abstract: 3D hand mesh reconstruction is a challenging yet essential task for downstream applications, including human-robot interaction and AR/VR. Although conve

tutorialsarxiv-cs-cv

Exploring the Temporal Consistency for Point-Level Weakly-Supervised Temporal Action Localization

arXiv:2602.05718v2 Announce Type: replace Abstract: Point-supervised Temporal Action Localization (PTAL) adopts a lightly frame-annotated paradigm (extit{i.e.}, labeling only a single frame per action

Fairness at Every Intersection: Uncovering and Mitigating Intersectional Biases in Multimodal Clinical Predictions

arXiv:2412.00606v2 Announce Type: replace Abstract: Biases in automated clinical decision-making using Electronic Healthcare Records (EHR) impose significant disparities in patient care and treatment

Local Ai

Fast-Convergent Meta-RL via Gradient-Clustered BS Sampling for Edge Caching

arXiv:2609.16370v1 Announce Type: cross Abstract: Wireless edge caching networks typically consist of many independent Base Stations (BSs), each facing its own request rate and content popularity prof

local-aiarxiv-cs-lg