Search: “framework”

GeoSkill:Experience-Driven Hierarchical Skill Learning with Collaborative Revision forGeospatialAgents

arXiv:2609.13667v1 Announce Type: new Abstract: Geospatial agents are increasingly expected to support recurring and evolving analytical tasks rather than execute isolated workflows. In such settings,

agentsarxiv-cs-ai

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Research

GradRepair-ODE: Certified Gradient Repair for Neural ODE Training

DGX agent

arXiv:2609.13204v1 Announce Type: cross Abstract: Neural ordinary differential equations use numerical solvers inside the training loop. The solver determines the forward trajectory and also affects t

researcharxiv-cs-cl

15 Sept 2026

GraMRAG: Orchestrating Multi-Agent Multi-Step Reasoning via Graph Memory with Reinforcement Learning

arXiv:2609.14066v1 Announce Type: cross Abstract: Although existing multi-agent Retrieval-Augmented Generation (RAG) systems have demonstrated promise on complex multimodal reasoning tasks, they remai

Applications

Graph Neural Networks for Influence Maximization in Social Networks: An Unsupervised Minimum Dominating Set Approach

arXiv:2609.13836v1 Announce Type: new Abstract: The Minimum Dominating Set (MDS) problem is a classic NP-hard combinatorial optimization problem with critical applications in social network analysis,

applicationsarxiv-cs-lg

GRAVA: Grounded Reasoning-to-Action Representation and Learning for Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2609.15169v1 Announce Type: new Abstract: Driving vision-language-action (VLA) models increasingly reason before acting, but their intermediate reasoning is often weakly grounded in physical sce

GroundBench: A Factorized, Counterfactual Benchmark for Locating VLM Affordance Failures

model-releasesarxiv-cs-cv

arXiv:2609.13308v1 Announce Type: new Abstract: A companion evaluation found that naming the target part in a manipulation prompt increased action accuracy by 0.32-0.63 across eight vision-language mo

GSLAD: Prototype-Regularized Graph Structure Learning for Multivariate Time Series Anomaly Detection

arXiv:2609.15483v1 Announce Type: new Abstract: Unsupervised multivariate time series anomaly detection methods typically identify anomalies through forecasting, reconstruction, or representation disc

Hardware-Aware Learned Representation Compression for Distributed In-Sensor Vision

arXiv:2609.13947v1 Announce Type: cross Abstract: In-sensor computing reduces the cost of transmitting high-resolution image data by performing early-stage processing near the sensor. However, the log

Harnessing Image Question Dependence for Better VLM Test-time Reinforcement Learning

arXiv:2609.13296v1 Announce Type: new Abstract: Test-time reinforcement learning can adapt vision-language models (VLMs) to unlabeled target data, but its effectiveness is fundamentally limited by the

safetyarxiv-cs-cv

HarnessVLN: Unifying Training-Free Embodied Navigation through an Agent Harness

arXiv:2609.15195v1 Announce Type: new Abstract: Embodied navigation requires agents to interpret visual observations, accumulate spatial knowledge, and execute actions to follow instructions or locate

agentsarxiv-cs-ro

HiGFRL: Hierarchical Graph Fusion-Driven Reinforcement Learning for Dependency-Aware Task Scheduling in Heterogeneous Cloud

arXiv:2609.14968v1 Announce Type: new Abstract: Online scheduling of dependency-aware tasks in heterogeneous cloud clusters is a fundamental yet challenging problem due to the complex interplay betwee

local-aiarxiv-cs-lg

High-Density Automated Valet Parking with Relocation-Free Sequential Operations

arXiv:2603.23803v2 Announce Type: replace-cross Abstract: In this paper, we present DROP, high-Density Relocation-free sequential OPerations in automated valet parking. DROP addresses the challenges i

researcharxiv-cs-ro

High-Probability Nash Regret for Decentralized Learning in Markov alpha-Potential Games: Episodic and Fully Online Asynchronous Algorithms with Applications to Markov Congestion Games

arXiv:2609.14959v1 Announce Type: new Abstract: We study decentralized learning of Nash equilibria (NE) in infinite-horizon discounted Markov games under bandit feedback, focusing on Markov alpha-pote

safetyarxiv-cs-lg

Hindsight-Anchored Policy Optimization: Learning Through Hindsight with Thompson Sampling-Inspired Adaptive Gating

arXiv:2603.11321v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards improves reasoning in large language models, yet on-policy learning often suffers from cold-sta

Horizon-specific Expert Fusion for Photovoltaic Power Forecasting

arXiv:2609.15035v1 Announce Type: new Abstract: Short-term photovoltaic power forecasting requires models to represent regular solar cycles and weather-driven fluctuations whose importance changes wit

HydroMap: Probabilistic Water Surface Elevation Mapping for Semantic Scene Representation in Inland Waterways

arXiv:2609.14903v1 Announce Type: new Abstract: Autonomous surface vehicles operating in inland waterways require a persistent representation of both surrounding structures and the water surface. LiDA

agentsarxiv-cs-ro

HypoEvolve: Genetic Algorithms Enable Multi-Agent LLMs to Discover Scientific Hypotheses

arXiv:2609.15938v1 Announce Type: new Abstract: Scientific agents contribute to hypothesis discovery by synthesizing evidence, assessing proposals, and developing new explanations. Recent systems comb

agentsarxiv-cs-cl

Identifying and Transferring Reasoning-Critical Neurons: Improving LLM Inference Reliability via Activation Steering

arXiv:2601.19847v3 Announce Type: replace Abstract: Despite the strong reasoning capabilities of recent large language models (LLMs), achieving reliable performance on challenging tasks often requires

researcharxiv-cs-cl

Impute-EM: Native Mixed-State Diffusion Models for Heterogeneous Data Imputation

arXiv:2609.15284v1 Announce Type: new Abstract: Missing values are ubiquitous in heterogeneous data mining, where numerical, categorical, and binary variables often coexist. Many imputation methods, e

Integrating Multi-view Multi-light Surface Reconstruction into Cultural Heritage Workflows

arXiv:2609.15833v1 Announce Type: new Abstract: Cultural heritage documentation increasingly relies on image-based 3D surface reconstruction, with photogrammetry software making such workflows accessi

researcharxiv-cs-cv

Inter-Rater Reliability of LLM and Rule-Based Annotation for Inferential Narrative Features: Three Studies on a Turkish Corpus

model-releasesarxiv-cs-cl

arXiv:2609.13936v1 Announce Type: new Abstract: Datasets that ship automatically generated feature annotations invite a question rarely asked of them: would a human agree with those labels? This repor

Is my model perplexed for the right reason? Contrasting LLMs' Benchmark Behavior with Token-Level Perplexity

model-releasesarxiv-cs-cl

arXiv:2603.29396v2 Announce Type: replace Abstract: Standard evaluations of Large language models (LLMs) focus on task performance, offering limited insight into whether correct behavior reflects appr

Joint Optimization for Federated Learning and Transmission over Unreliable Wireless Networks with Heterogeneous Data

model-releasesarxiv-cs-lg

arXiv:2609.14246v1 Announce Type: cross Abstract: In wireless federated learning (FL), data heterogeneity and multiple local updates induce client drift, degrading model convergence. It is further aff

JSolver: Joint Spectrum Estimation and Multi-Material Decomposition from Single-Energy CT Projections

arXiv:2505.08123v2 Announce Type: replace-cross Abstract: Multi-material decomposition (MMD) enables quantitative reconstruction of tissue compositions in the human body, supporting a wide range of cl

LabAgent: Customize Any Research Hubs for Scientific Discoveries Using AI Agents

arXiv:2609.13437v1 Announce Type: new Abstract: Scientific research is a continuous process that emphasizes inheritance. Methods developed by predecessors are often expanded upon by new researchers to

Language-Guided Representation Learning for Robust Cross-Sensor Material Recognition

model-releasesarxiv-cs-cl

arXiv:2609.14783v1 Announce Type: cross Abstract: Robots need touch to manipulate objects safely and reliably, as many properties, such as softness, texture, and contact stability, are hard to infer f

Learning Agile Flight Maneuvers: Deep SE(3) Motion Planning and Control for Quadrotors

arXiv:2209.11097v2 Announce Type: replace Abstract: Agile flights of autonomous quadrotors in cluttered environments require constrained motion planning and control subject to translational and rotati

safetyarxiv-cs-ro

Learning-Based Dynamic Obstacle Avoidance for a UAV Using Only Three Range Sensors

arXiv:2609.14426v1 Announce Type: new Abstract: We present a learning-based approach to kinodynamic online motion planning for an Unmanned Aerial Vehicle (UAV) operating at a fixed altitude in unknown

local-aiarxiv-cs-ro

Learning Continuous Source Responses For Generalizable AI-Generated Image Detection

arXiv:2609.14316v1 Announce Type: new Abstract: Advances in image generation have made synthetic images increasingly difficult to distinguish from real photographs, raising concerns about the trustwor

researcharxiv-cs-cv

Applications

Learning In-Hand Object Reaching to General 6D Poses

arXiv:2609.13761v1 Announce Type: new Abstract: In-hand manipulation allows multi-fingered dexterous hands to reconfigure grasped objects without releasing and regrasping them. This improves manipulat

applicationsarxiv-cs-ro

Tutorials

Learning Metastable Dynamics

arXiv:2609.14712v1 Announce Type: cross Abstract: Metastability---a phenomenon where systems remain trapped in quasi-stable states before abruptly transitioning under rare perturbations---is ubiquitou

tutorialsarxiv-cs-lg

Learning Multimodal One-step Flow Policy via Value-weighted Optimal Transport

arXiv:2609.15883v1 Announce Type: cross Abstract: Offline reinforcement learning aims to learn a policy solely from fixed datasets, which often contain multimodal action distributions. Flow policies c

Tutorials

Learning to Coach for Experiential Learning

arXiv:2609.15851v1 Announce Type: new Abstract: Language models can learn from experience, but raw solution trajectories are often too long and noisy to provide effective guidance. In this work, we pr

tutorialsarxiv-cs-cl

Learning to Solve Stochastic Controls with Unknown Drifts and Running Rewards: Theory, Algorithms and Convergence

arXiv:2609.14972v1 Announce Type: new Abstract: We study continuous-time and possibly high-dimensional stochastic control problems where drift coefficients and running reward functions are unknown. Du

safetyarxiv-cs-lg

Lie to me: Detecting Managerial Evasiveness in Earnings Calls via Conversational Audio Encoders

arXiv:2609.13893v1 Announce Type: new Abstract: Earnings conference calls are a primary channel through which managers disclose information under analyst scrutiny. Prior work has linked vocal and lexi

Lightning Weave: Improving the Accuracy-Efficiency Frontier of Reasoning Models through Capability Composition

model-releasesarxiv-cs-ai

arXiv:2609.14708v1 Announce Type: new Abstract: A core goal of efficient reasoning is to improve the accuracy-efficiency frontier. However, jointly improving reasoning accuracy and inference efficienc

Look Before You Leap: Factual Decoding with Internal Attribution Signals

arXiv:2609.15745v1 Announce Type: cross Abstract: Hallucination remains a critical challenge in large language models (LLMs), where early factual errors compound through autoregressive generation in a

Applications

LORE: Jointly Learning the Intrinsic Dimensionality and Relative Similarity Structure From Ordinal Data

arXiv:2602.04192v3 Announce Type: replace Abstract: Learning the intrinsic dimensionality of subjective perceptual spaces such as taste, smell, or aesthetics from ordinal data is a challenging problem

applicationsarxiv-cs-lg

Hardware

LynnReal-Omni: Native multi-modal Video Generation for Agentic Visual Workflows

arXiv:2609.15863v1 Announce Type: new Abstract: Video diffusion models are stochastic and hard to control: precise content often requires repeated sampling without guaranteed success, and long-horizon

hardwarearxiv-cs-cv

MANE: A Multi-Path Adaptive Network for Edge Onloading of Deep Neural Networks

arXiv:2609.14660v1 Announce Type: cross Abstract: Split computing constitutes a widely used distributed inference approach, where a lightweight head model is onloaded onto the device and a heavier tai

local-aiarxiv-cs-ai

MARC: Morphology-Aware Regression of Consensus for Cell Segmentation in Subcellular Spatial Transcriptomics

arXiv:2609.13665v1 Announce Type: new Abstract: Accurate cell segmentation remains a major bottleneck in subcellular spatial transcriptomics (SST), in which morphological images and spatially resolved

local-aiarxiv-cs-cv

MARCUS: An agentic, multimodal vision-language model for cardiac diagnosis and management

model-releasesarxiv-cs-ai

arXiv:2603.22179v2 Announce Type: replace Abstract: Cardiovascular disease remains the leading cause of global mortality, with progress hindered by human interpretation of complex cardiac tests. Curre

MarKey: Marginal Utility Guided Greedy Keyframe Selection for Long Video Understanding

arXiv:2609.15408v1 Announce Type: cross Abstract: Long-video understanding remains challenging for multimodal large language models (MLLMs) because densely encoding long frame sequences is computation

researcharxiv-cs-cl

Mask, Sample, Revise: A Revisable CTMC Inference Stack for Guided Discrete Flow Matching Text-to-Speech

arXiv:2606.13989v2 Announce Type: replace-cross Abstract: Recent alignment-free non-autoregressive (NAR) text-to-speech (TTS) models formulate synthesis as a conditional infilling task, bypassing expl

MAST: Label-Efficient, Robust, and Generalizable Sound Detection for Biodiversity Monitoring via Masked Audio Pretraining and Self-Training

arXiv:2609.15221v1 Announce Type: cross Abstract: Passive acoustic monitoring can measure biodiversity at larger scales, but time--frequency annotation of animal vocalizations is expensive, site-speci

Hardware

MedDiME: Efficient Latent Diffusion with Adaptive Masking for Medical Counterfactual Generation

arXiv:2609.15647v1 Announce Type: new Abstract: Medical counterfactual generation modifies images to change model predictions for interpretability. However, existing diffusion-based approaches are oft

hardwarearxiv-cs-cv

MedSAM3: Delving into Segment Anything with Medical Concepts

arXiv:2511.19046v2 Announce Type: replace-cross Abstract: Medical image segmentation is fundamental for biomedical discovery. Existing methods lack generalizability and demand extensive, time-consumin

agentsarxiv-cs-ai

Mesh-based Super-resolution of Multiscale Detonation Flows with Graph Transformers

arXiv:2511.12041v4 Announce Type: replace-cross Abstract: Super-resolution flow reconstruction using state-of-the-art data-driven techniques is valuable for a variety of applications, such as subgrid/