Search: “models”

Planned Test-Time Scaling with Coordinated Reasoning Paths

arXiv:2609.27374v1 Announce Type: cross Abstract: Test-time scaling with parallel branches is widely adopted to improve performance on challenging reasoning tasks. The predominant approach, repeated s

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Probabilistic and Geometry Aware Neural Surrogate of Scrape Off Layer Plasma Simulations

DGX agent

arXiv:2609.28116v1 Announce Type: new Abstract: Fast surrogates for tokamak boundary-plasma simulation are typically deterministic regressors mapping a global operating point to a flattened vector of

researcharxiv-cs-lg

24 Sept 2026

Reliable Fusion of Conflicting Experts

arXiv:2609.27913v1 Announce Type: new Abstract: We study the problem of aggregating opinions from multiple black-box experts in noisy, conflict-prone settings where expert reliability varies across in

Remote Surfaces at Your Fingertips: Electrovibration-Based Tactile Feedback for Robot Teleoperation via Touchscreen Interfaces

arXiv:2609.27938v1 Announce Type: new Abstract: Enabling operators to perceive and interact with remote environments naturally is a fundamental challenge in robotic teleoperation. This is especially c

safetyarxiv-cs-ro

Agents

RexDrug: Reliable Multi-Drug Combination Extraction through Reasoning-Enhanced LLMs

arXiv:2603.08166v2 Announce Type: replace Abstract: Automated Drug Combination Extraction (DCE) from large-scale biomedical literature is crucial for advancing precision medicine and pharmacological r

agentsarxiv-cs-cl

Safe Multi-Robot Coordination via VLM-LLM Reasoning and Reachability Analysis

arXiv:2609.27816v1 Announce Type: cross Abstract: Safe coordination in heterogeneous machine-to-machine (M2M) robotic systems is challenging when robots differ in sensing capabilities, environmental a

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SatUnreal: A High-Precision Synthetic Dataset for Satellite Stereo Matching via Unreal Engine

arXiv:2609.27442v1 Announce Type: new Abstract: 3D reconstruction from satellite imagery is essential for large-scale topographic analysis, yet the lack of high-fidelity training datasets with accurat

applicationsarxiv-cs-cv

Temporally Ordered Region-Token Mamba with Logit-Space Diffusion for Remote Sensing Change Detection

arXiv:2609.27149v1 Announce Type: new Abstract: Remote sensing change detection requires both global reasoning across bitemporal images and precise localization of changed regions. However, dense atte

local-aiarxiv-cs-cv

Vision-Based Control of a Tether-Suspended Aerial Radiation Sensing Payload

arXiv:2609.27219v1 Announce Type: new Abstract: Aerial radiation surveys achieve higher sensitivity when the radiation detector is held close to the ground. Detector sensitivity falls off roughly with

researcharxiv-cs-ro

'What's That Sound?': A Versatile, Robust, and Lightweight Convolutional Transformer for Environment Sound Recognition

arXiv:2609.27762v1 Announce Type: cross Abstract: The conventional hearing aid is both costly and lim- ited in usage, as it is not intended to detect non-speech audio. Our objective is to develop a ma

safetyarxiv-cs-lg

Zero-Shot Object Removal via Attention Masking, Latent Anchoring, and Refinement

arXiv:2609.28342v1 Announce Type: new Abstract: Removing an object from a real image requires more than synthesizing plausible content within a mask: the method must suppress residual object features,

Tutorials

A digital-twin framework for forecasting treatment-day imaging with contour uncertainty in adaptive proton radiotherapy

arXiv:2609.24725v1 Announce Type: cross Abstract: Head-and-neck anatomy changes over a six-to-seven-week proton course, and the anatomy of a later week cannot be imaged when the plan is made. We prese

tutorialsarxiv-cs-ai

ACLArena: Agent Continue Learning in Multi-stage Post-training

arXiv:2609.23989v1 Announce Type: new Abstract: Building general-purpose agents for industrial deployment requires integrating multiple capabilities, each typically acquired at a distinct stage of tra

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Beyond Scalar Sensitivity: Activation-Aware Mixed-Precision LLM Quantization with Cross-Layer Refinement

arXiv:2609.25916v1 Announce Type: new Abstract: Mixed-precision weight quantization is commonly formulated as a Multiple-Choice Knapsack Problem (MCKP), yet existing solvers rely on scalar sensitivity

local-aiarxiv-cs-lg

Complementary Roles of Radiomics and Foundation Representations in Renal Cell Carcinoma Classification: A Comparative Study of 2D and 3D CT Encodings

arXiv:2609.26463v1 Announce Type: new Abstract: Accurate preoperative subtype classification of renal cell carcinoma (RCC) from contrast-enhanced computed tomography remains clinically challenging. Ra

Damage Predicts Recovery: When Calibration Data Matters in Compressing Financial LLMs

arXiv:2609.26241v1 Announce Type: new Abstract: Post-training quantization and pruning rely on a small calibration corpus. Whether specialized domains such as finance require domain-matched calibratio

applicationsarxiv-cs-cl

DeepFEAv2: Deep Learning for Transient Finite Element Analysis Beyond Structured Meshes

arXiv:2609.26426v1 Announce Type: new Abstract: Finite Element Analysis (FEA) is widely used for transient mechanical simulations, but its high computational cost limits real-time and high-resolution

Designing and Analysing Argument Mining Pipelines: Towards a Comprehensive Assessment

arXiv:2609.26338v1 Announce Type: new Abstract: Argument Mining (AM) transforms natural language into its underlying argument structures. This transformation is typically realized through a sequence o

researcharxiv-cs-cl

End-to-End Quantum Semantic Communication with Variational Quantum Neural Networks

arXiv:2609.25044v1 Announce Type: cross Abstract: This paper presents a quantum semantic communication (QSemCom) framework combining quantum machine learning (QML) and semantic communication (SemCom).

Explanation-Guided Medical Named Entity Recognition with Stability and Boundary Awareness for Atopic Dermatitis

arXiv:2606.22886v2 Announce Type: replace Abstract: Objective: This study aims to improve the reliability and robustness of medical named entity recognition (NER) in Chinese atopic dermatitis (AD) cli

local-aiarxiv-cs-cl

From Offline Proxies to Online Decisions: A Layered Engagement Evaluation Framework for Conversational AI

arXiv:2609.25408v1 Announce Type: cross Abstract: Online A/B experiments are the decision standard for user engagement, but traffic and readout time limit how many conversational-AI changes can be tes

Geometric and Semantic Coupling for Interaction Understanding in 3D Scenes

arXiv:2609.25247v1 Announce Type: new Abstract: Interaction understanding in 3D scenes requires a joint description of movable parts, their motion, and the regions through which they can be operated.

Agents

GRUET: Quantifying Uncertainty of Agentic Reasoning-and-Acting Processes

arXiv:2609.24831v1 Announce Type: new Abstract: Agents have attracted considerably increasing attention due to the power of executing both Reasoning and Acting (ReAct) in open and dynamic environments

agentsarxiv-cs-ai

Hyperbolic Restricted Boltzmann Machine Neural Quantum State

arXiv:2609.26032v1 Announce Type: cross Abstract: We construct the first type of non-Euclidean non-autoregressive neural quantum state (NQS) in the form of the hyperbolic Restricted Boltzmann Machine

Information-Theoretic Decoupled Prompt Tuning for Continual Learning

arXiv:2609.26257v1 Announce Type: new Abstract: Continual learning (CL) aims to incrementally acquire knowledge from sequential data while avoiding catastrophic forgetting. Recently, prompt tuning has

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JAMB: Joint Action-Motion Diffusion for Bimanual Manipulation

arXiv:2609.25322v1 Announce Type: new Abstract: Coordinated bimanual manipulation is challenging because the motion of either arm can alter the shared 3D scene and thereby affect the other arm. Yet mo

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Leaky-integrator reconstruction: taming error accumulation in recursive differenced time-series forecasting

arXiv:2609.23378v1 Announce Type: new Abstract: We introduce leaky-integrator reconstruction, a training-free method that cures the error accumulation of recursive differenced forecasting. Our first c

researcharxiv-cs-ai

Learning Defensive Policies against Diverse Inference Attacks for Smart Meter Privacy

arXiv:2609.25484v1 Announce Type: new Abstract: Smart meter (SM) data provides fine-grained visibility into household energy consumption, but also exposes users to privacy risks. Inference attacks, kn

applicationsarxiv-cs-lg

Tutorials

Less Is More in the Long Tail: Stage-Adaptive Sample Selection for Annotation-Efficient Dense Prediction

arXiv:2609.25850v1 Announce Type: new Abstract: Deep learning performance generally improves with increasing training data, yet this scaling is fundamentally constrained by annotation cost in large-sc

tutorialsarxiv-cs-cv

LiDAS: Lighting-driven Dynamic Active Sensing for Nighttime Perception

arXiv:2512.08912v2 Announce Type: replace-cross Abstract: Nighttime environments pose significant challenges for camera-based perception, as existing methods passively rely on the scene lighting. We i

applicationsarxiv-cs-ro

MIND the Gap: A Geographic Implicit Neural Representation with Adjustable Spatial Scale

arXiv:2609.25454v1 Announce Type: cross Abstract: Geographic measurements are often sparse, leaving large areas without labels for the quantities we want to map. Geographic implicit neural representat

Mode Collapse Is Cheap to Detect: A Ground-Truth-Free Pre-Flight Check for Neural Samplers

arXiv:2609.26272v1 Announce Type: new Abstract: Neural samplers are trained against an unnormalised target ildepi=e^{-E} with no samples from pi, which leaves the practitioner with no way to tell whet

Neoadjuvant chemotherapy response prediction using pretreatment diffusion and contrast-enhanced magnetic resonance imaging with clinical variables

arXiv:2609.26105v1 Announce Type: cross Abstract: Prediction of pathological complete response before neoadjuvant chemotherapy may facilitate more tailored therapeutic planning for breast cancer patie

OV-MAP: Open-Vocabulary Zero-Shot 3D Instance Segmentation Map for Robots

arXiv:2506.11585v3 Announce Type: replace Abstract: We introduce OV-MAP, a novel approach to open-world 3D mapping for mobile robots by integrating open-features into 3D maps to enhance object recogni

applicationsarxiv-cs-cv

PAANI : On Device Visual Evidence Fusion and Explainable Guidance for River Robot Simulation

arXiv:2609.22353v1 Announce Type: new Abstract: Mobile river monitoring robots must interpret obstacles and water boundaries that geographic waypoints alone cannot describe. On resource constrained pl

local-aiarxiv-cs-ai

Partially Observed Sparse Graphs: The Unknown Sampling Rate is a Tail Index

arXiv:2609.26199v1 Announce Type: new Abstract: A large graph is often available only in part: a crawl stopped by its budget, a panel, a partial dump. When the sampled fraction s is known by design th

PartLLM: A Unified Multimodal Foundation for 3D Part Segmentation

arXiv:2609.25832v1 Announce Type: new Abstract: Part segmentation is a fundamental problem in computer graphics and 3D vision. Recent works have expanded 3D part segmentation beyond fixed taxonomies,

PatchKV: Efficient KV Cache Recovery for Dynamically Edited LLM Contexts

arXiv:2609.26219v1 Announce Type: cross Abstract: Long-running LLM agent workflows often revise interior context spans while retaining long suffixes. Although suffix tokens remain unchanged, altered c

local-aiarxiv-cs-lg

Physics-guided deep metric learning with continuous time embeddings for open-world radar pulse de-interleaving

arXiv:2609.25057v1 Announce Type: cross Abstract: Radar pulse de-interleaving is a foundational Electronic Support Measures (ESM) task that aims to separate chronologically interleaved pulse streams f

Predicting Postprandial Glycemic Response from Meal Images, Clinical Variables, and Gut Microbiome Information

arXiv:2609.24453v1 Announce Type: new Abstract: Predicting postprandial glycemic response (PPGR) is fundamental to personalized nutrition and type 2 diabetes management, yet existing approaches typica

applicationsarxiv-cs-ai

Prompt Breadth and Rollout Refresh Interact in On-Policy Distillation

arXiv:2609.25048v1 Announce Type: new Abstract: How many prompts does on-policy distillation (OPD) need, and how does the answer depend on the student policies that generate its training responses? We

safetyarxiv-cs-cl

Radiomics--Foundation Fusion for Interpretable RCC Classification: Internal Benchmarking and Exploratory External Transfer

arXiv:2609.26578v1 Announce Type: new Abstract: Accurate preoperative subtype classification of renal cell carcinoma (RCC) from contrast-enhanced CT remains clinically challenging because clear cell R

Real-Time Atomic-Resolution Electron Phase Imaging without Probe Calibration via Ptychography-Supervised Learning

arXiv:2609.25684v1 Announce Type: new Abstract: Atomic-scale phase imaging is central to resolving defects, interfaces, and weakly scattering atoms that govern the behavior of nanoscale materials. Ele

local-aiarxiv-cs-cv

Recovering Lost Details: Multi-Scale Frequency Compensation for Long-Term Time Series Forecasting

arXiv:2609.24229v1 Announce Type: new Abstract: Long-term time series forecasting has made significant progress by leveraging multi-scale information to capture hierarchical temporal patterns and mode

applicationsarxiv-cs-ai

Robust Active-Perception Control for Global-State-Free Aerial-Ground Cooperation

arXiv:2609.25898v1 Announce Type: new Abstract: Aerial-ground cooperation requires real-time UAV--UGV relative-state information. Instead of maintaining global estimates for both robots, direct contro

local-aiarxiv-cs-ro

Robust Photoplethysmography Signal Denoising via Mamba Networks

arXiv:2510.11058v2 Announce Type: replace Abstract: Photoplethysmography (PPG) is widely used in wearable health monitoring, but its reliability is often degraded by noise and motion artifacts, limiti

applicationsarxiv-cs-lg

Semantic-Anchored Evidential Fusion for Domain-Robust Whole-Slide Survival Analysis

arXiv:2606.19966v2 Announce Type: replace-cross Abstract: Whole-slide images (WSIs) are widely used for computational cancer prognosis. However, most existing methods primarily focus on in-domain perf

SPECTRA: Adaptive Execution of Speculative Decoding on a Runtime-Reconfigurable Tiled Architecture

arXiv:2609.24847v1 Announce Type: cross Abstract: LLM inference on edge devices is constrained by computational and memory resources, making efficient autoregressive decoding challenging. Speculative

researcharxiv-cs-ai