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Distance to Class Prototypes: Active Learning for Object Detection

arXiv:2609.20248v1 Announce Type: new Abstract: Deploying a deep object detector in a new setting is limited less by architecture than by the cost of annotating data from that setting. Active learning

researcharxiv-cs-cv

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Human DGX agent

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Distributed Event-Triggered Distance-Based Formation Control for Multi-Agent Systems

DGX agent

arXiv:2509.12390v3 Announce Type: replace Abstract: This paper addresses collaborative formation control for multi-agent systems with limited resources. We consider a team of robots tasked with achiev

agentsarxiv-cs-ro

18 Sept 2026

Distributed Model Predictive Control with Connectivity-based Contracts

arXiv:2609.19912v1 Announce Type: new Abstract: Teams of mobile robots rely on continuous communication with their neighbors for coordination, yet most distributed model predictive control (DMPC) sche

agentsarxiv-cs-ro

Distributionally Robust Federated Learning with Multi-Source Data

arXiv:2609.20501v1 Announce Type: new Abstract: Federated learning trains a shared model from private client data. In practice, data-generating distributions may differ, and the true mixture across cl

DITTO: Dexterous Interface for Transparent TeleOperation

arXiv:2609.19196v1 Announce Type: new Abstract: Collecting data for manipulation with high-DOF hands is challenging, as interfaces must capture rich hand motion while rendering the contact interaction

Do AI Agents Understand Computer Architecture?

arXiv:2609.19387v1 Announce Type: new Abstract: Agents are increasingly asked to design hardware, and increasingly reported to succeed. Such reports establish that a design improved; they cannot estab

agentsarxiv-cs-ai

DocAttriBench: Benchmarking Answer Grounding in Document Visual Question Answering

model-releasesarxiv-cs-cv

arXiv:2609.20574v1 Announce Type: new Abstract: Answer grounding in document visual question answering remains an open challenge: most benchmarks lack grounding annotations or provide limited-quality

Don't Mask the Environment: Observation Supervision Changes How Agents Explore Under RL

arXiv:2609.20715v1 Announce Type: cross Abstract: Agent trajectories record what an agent does and what happens next. Yet standard supervised fine-tuning (SFT) applies loss only to agent-authored acti

dQwen3.5: Hybrid-Attention Diffusion Language Models

arXiv:2609.20751v1 Announce Type: new Abstract: Adapting a pretrained autoregressive (AR) model is a cost-efficient route to a diffusion language model (DLM). While nearly all such adaptations start f

researcharxiv-cs-cl

DR-MPC: Fast and Feasible Dynamics-Relaxed Model-Predictive Control for Legged Locomotion

arXiv:2609.20035v1 Announce Type: new Abstract: This paper presents dynamics-relaxed model predictive control (DR-MPC), a novel MPC formulation for legged locomotion, and a tailored interior-point met

Drag-Aware Aerodynamic Manipulability for Torque-Limited Redundant Multirotors: Aerodynamic Promptness based on the Symmetric Acceleration Capacity

model-releasesarxiv-cs-ai

arXiv:2603.07998v2 Announce Type: replace-cross Abstract: Aerodynamic promptness quantifies how rotor-speed variations generate multirotor wrench variations, but its Euclidean formulation assigns the

Dual-Axis Policy Optimization for LLM Agents: Bayesian Feedback Attribution and Trajectory Mass Normalization

arXiv:2609.19830v1 Announce Type: new Abstract: Reinforcement learning for LLM agents involves two distinct optimization di- mensions: how environment feedback is exploited within a trajectory, and ho

Dynamic Generalized Gromov-Wasserstein Optimal Transport

arXiv:2609.20008v1 Announce Type: cross Abstract: Gromov--Wasserstein optimal transport (GW-OT) extends classical optimal transport by introducing structure-aware transport cost. This is particularly

Dynamic-LIVO: A Dynamic-Aware LiDAR-Inertial-Visual Odometry System Using Spatio-Temporal Normals

model-releasesarxiv-cs-ro

arXiv:2609.19336v1 Announce Type: new Abstract: This paper proposes Dynamic-LIVO, a dynamic-aware LiDAR-Inertial-Visual Odometry (LIVO) system for robust state estimation and static colored mapping in

DynaWeightPnP: Toward global real-time 3D-2D solver in PnP without correspondences

arXiv:2409.18457v2 Announce Type: replace Abstract: This paper addresses a special Perspective-n-Point (PnP) problem: estimating the optimal pose to align 3D and 2D shapes in real-time without corresp

safetyarxiv-cs-cv

E-AVI: Evidence-Grounded Multimodal Assessment for Automated Video Interviews

arXiv:2609.20001v1 Announce Type: new Abstract: Automated video interview assessment integrates verbal content, acoustic delivery, and visual behavior, yet numerical predictions alone provide limited

researcharxiv-cs-ai

Local Ai

Earth Surface Immune System for Rapid Monitoring of Unknown Anomalies

arXiv:2609.20662v1 Announce Type: new Abstract: Earth surface anomalies, driven by escalating climate change, and expanding human activities, are increasing in both frequency and diversity, yet their

local-aiarxiv-cs-cv

EconSkills: Studying Skill Transfer and Retrieval for Web Agents on Live Economic Data

arXiv:2609.19523v1 Announce Type: new Abstract: Web agents often revisit the same sites, yet most evaluations discard the procedures learned in earlier successful interactions. We introduce EconSkills

agentsarxiv-cs-ai

Edustories: A Collection of Real-world Case Studies from Classroom Practices

arXiv:2609.20484v1 Announce Type: cross Abstract: Despite the widely recognized potential of AI in education, most prior work has focused on individualized student assistance. In contrast, the majorit

applicationsarxiv-cs-ai

Effective and Efficient Threat Hunting with Small Language Models

model-releasesarxiv-cs-ai

arXiv:2512.06660v3 Announce Type: replace-cross Abstract: Analysts in Security Operations Centers query massive telemetry streams using Kusto Query Language (KQL), but writing correct KQL demands spec

Efficient Nash Equilibrium Computation for Cybersecurity Games

arXiv:2609.19399v1 Announce Type: cross Abstract: Computing Nash equilibria of simulation-based cybersecurity games with policy-space response oracles (PSRO) is bottlenecked by payoff estimation: ever

Efficient Unified Multimodal Understanding (EUMU): Winning Solution for the MUMU Track at the 8th LSVOS Challenge

arXiv:2609.19451v1 Announce Type: new Abstract: The Mobile Unified Multimodal Understanding (MUMU) Challenge requires a single efficient model to jointly perform multi-concept image tagging, open-voca

researcharxiv-cs-cv

Efficiently Distributed Federated Learning

arXiv:2609.19972v1 Announce Type: cross Abstract: Federated Learning (FL) is experiencing a substantial research interest, with many frameworks being developed to allow practitioners to build federati

researcharxiv-cs-ai

Efficiently Linking Unstructured Data for Multi-step Reasoning

arXiv:2609.19491v1 Announce Type: cross Abstract: Modern LLMs and AI agents increasingly support data engineering workflows that integrate evidence from unstructured sources. Such pipelines typically

agentsarxiv-cs-ai

Elastic Spectral State Space Models for Train-Once Budgeted Inference

arXiv:2601.22488v3 Announce Type: replace Abstract: Modern sequence models are typically trained at a fixed computational capacity, while real-world applications require deployment across platforms wi

EliGSiR: Continual RGB-D Mapping with Gaussian Splatting under Bounded Compute

arXiv:2609.20348v1 Announce Type: new Abstract: Conventional 3D Gaussian Splatting assumes a closed set of observations and long optimization schedules. Continual RGB-D mapping in contrast poses the p

researcharxiv-cs-cv

Embedding Models Measure in Peculiar Ways

arXiv:2609.20821v1 Announce Type: new Abstract: Embedding spaces define notions of semantic similarity and distance. We study whether those embeddings reflect physical measurements of mass, distance,

safetyarxiv-cs-cl

EmbodiedMind: Adaptive Data Curation and Prefix-Tree Reinforcement Learning for Efficient Embodied Intelligence

arXiv:2609.19659v1 Announce Type: cross Abstract: Training embodied foundation models typically requires massive-scale datasets and extensive computational resources, yet often suffers from three crit

Emergent interactions lead to collective frustration in robotic matter

arXiv:2507.22148v3 Announce Type: replace-cross Abstract: Artificial intelligence and robotic systems are increasingly deployed as interacting collectives of learning agents. This raises the question

Enabling automatic transcription of child-centered audio recordings from real-world environments

arXiv:2506.11747v2 Announce Type: replace-cross Abstract: Longform audio recordings obtained with microphones worn by children-also known as child-centered daylong recordings-have become a standard me

applicationsarxiv-cs-lg

Enhanced Agriculture-informed Neural Network by Domain Knowledge

arXiv:2609.19466v1 Announce Type: new Abstract: Accurate prediction of nitrous oxide (N2O) emissions from agriculture is important for assessing environmental impacts and supporting sustainable farmin

Enhanced Knowledge Distillation for Detection Transformer via Teacher Prediction Refinement

arXiv:2609.19964v1 Announce Type: new Abstract: Detection Transformers (DETRs) achieve strong performance in object detection but remain challenging to deploy on edge devices due to their high computa

applicationsarxiv-cs-cv

Enhancing the Perception of Safety and Comfort during Physical Human-Robot Handshake Interactions by Integrating Flexible Elements into a Robotic Arm

arXiv:2609.19375v1 Announce Type: new Abstract: Safety and comfort in human-robot physical in-teractions are essential aspects in the development of social technologies, where natural gestures, such a

safetyarxiv-cs-ro

Epidemiological Causal Graph Identification: Challenges, Identifiability and Algorithms

arXiv:2609.20676v1 Announce Type: new Abstract: Causal discovery from observational data is fundamental to statistics and machine learning, yet determining causal direction without interventions neces

Local Ai

EPIG-Tree: Compute-Optimal Branching for Gradient-Efficient Reinforcement Learning

arXiv:2609.20004v1 Announce Type: cross Abstract: Reward-based reinforcement learning for language models, exemplified by Group Relative Policy Optimization (GRPO), collapses an entire stochastic traj

local-aiarxiv-cs-ai

Equivariant Filter Design for Acoustic and Depth Aided Inertial Navigation Systems

model-releasesarxiv-cs-ro

arXiv:2609.19742v1 Announce Type: new Abstract: Autonomous Underwater Vehicles (AUVs) navigating without GPS typically fuse inertial measurements with acoustic Doppler Velocity Log (DVL) velocities an

ERCPMP-Gx: Endoscopic Image and Video Dataset for Morphological, Histopathological, and Genomic Characterization of Colorectal Polyposis

model-releasesarxiv-cs-ai

arXiv:2609.20815v1 Announce Type: cross Abstract: Hereditary polyposis syndromes can be precursor lesions to colorectal cancer and are associated with a broad spectrum of extracolonic tumors. Early id

Error bounds in Sobolev norms for approximations with norm constrained ReLU neural networks

arXiv:2609.19937v1 Announce Type: cross Abstract: Recent studies have shown that smooth functions can be well approximated by ReLU neural networks with path norm constraint on the weights. We extend t

Estimation of multiple mean vectors in high dimension

arXiv:2403.15038v3 Announce Type: replace-cross Abstract: We endeavour to estimate numerous multi-dimensional means of various probability distributions on a common space based on independent samples.

applicationsarxiv-cs-lg

Evaluating Communicative Success in Machine-Translated Conversation

model-releasesarxiv-cs-cl

arXiv:2609.19885v1 Announce Type: new Abstract: Interpreter agents built on machine translation (MT) increasingly mediate live conversation between people who do not share a language, yet we still eva

Local Ai

Evaluating Explanation Methods by the Predictors They Induce

arXiv:2609.20058v1 Announce Type: new Abstract: Explanations of machine learning models are usually judged by criteria that are hard to compare. We propose a simpler test: if an explanation really des

local-aiarxiv-cs-lg

Evaluating Financial Sentiment in the Age of AI

arXiv:2609.20198v1 Announce Type: new Abstract: Financial sentiment measures are widely used in empirical finance, but it remains unclear whether general-purpose large language models (LLMs) improve o

applicationsarxiv-cs-lg

Evaluating Out-of-Distribution Robustness in Graph-Based Android Malware Classification: A New Principled Benchmark

arXiv:2508.06734v3 Announce Type: replace-cross Abstract: While graph-based Android malware classifiers report strong benchmark accuracy of over 94%, their performance sharply decreases up to 45% when

EviRec: Continual Evidence Learning for Dual Cold-Start POI Recommendation

arXiv:2609.20313v1 Announce Type: new Abstract: Point-of-Interest (POI) recommendation is a core task in location-based services, yet most existing methods assume a fixed user population and POI catal

Evolution or Illusion? Rethinking Evaluation in LLM Evolutionary Search

arXiv:2609.19799v1 Announce Type: cross Abstract: LLM-driven evolutionary search finds programs by launching seeds and iterating each one. Papers report a single budget setting, usually one seed run f

researcharxiv-cs-ai

Execution-Aware Pre-Execution Ranking for Grasp-Conditioned Robotic Placement

arXiv:2609.19946v1 Announce Type: new Abstract: A geometrically valid placement can still be difficult to execute because the selected grasp changes the required end-effector pose, collision geometry,

Expected Hypervolume Maximization for Multiobjective Optimization under Uncertainties

arXiv:2609.19858v1 Announce Type: new Abstract: The problem of multiobjective optimization under uncertainties is often approached by taking the expectation of each objective. In this work, we propose

Explaining spatial information flow in short-term traffic forecasting models using a gated graph attention network

arXiv:2609.20217v1 Announce Type: new Abstract: Short-term traffic forecasting supports real-time monitoring and control of road networks, and graph attention networks (GAT) are the standard means of