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MTMed3D: A Multi-Task Transformer-Based Model for 3D Medical Imaging

arXiv:2511.12373v2 Announce Type: replace-cross Abstract: In the field of medical imaging, AI-assisted techniques such as object detection, segmentation, and classification are widely employed to alle

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Multivariate quantile regression via Kolmogorov-Arnold Networks

DGX agent

arXiv:2609.23906v1 Announce Type: new Abstract: This paper introduces a novel algorithm for predicting conditional joint distributions of vector-valued targets in stochastic systems whose randomness i

researcharxiv-cs-lg

22 Sept 2026

NaRPA: Navigation and Rendering Pipeline for Astronautics

arXiv:2211.01566v2 Announce Type: replace-cross Abstract: This paper presents the applications of scientific ray-tracing in modeling and simulating light transport for space-borne image data generatio

NLPCC 2026 Task 10: Citation-Level Faithfulness Verification with DeBERTa Ensembles and Class-Wise Calibration

arXiv:2609.22774v1 Announce Type: new Abstract: This paper presents our system for Track 2 of the NLPCC 2026 Shared Task 10 on citation-level faithfulness in AI-assisted scientific reporting. Given an

Not All Ranks Are Equal: Budget-Aware LoRA Merging Across Tasks

arXiv:2609.22237v1 Announce Type: new Abstract: Merging low-rank adapters (LoRAs) promises to eliminate the overhead of swapping task-specific weights at inference time. However, existing merging meth

Not All Task Vectors Need Equal Rank: Energy-Proportional Allocation for Model Merging

arXiv:2609.24517v1 Announce Type: cross Abstract: Model merging aims to combine multiple fine-tuned models derived from a common pretrained model into a single multi-task model without additional join

Object-Centered Reconstruction for Vision-Based 3D Force Estimation

arXiv:2609.23856v1 Announce Type: new Abstract: Excessive force may damage tissue and increase the risk of anastomotic leakage in robotic colorectal surgery. Although the da Vinci 5 provides force sen

Observational Equivalence of LLM and Human Annotation

arXiv:2609.22133v1 Announce Type: new Abstract: In this paper, we show that LLM and human coding are observationally equivalent in terms of annotation quality: recent LLMs agree with expert coders at

Odometry-Aided Real-Time Mapping for Underwater Robots Using Forward-Looking Sonar

arXiv:2609.24195v1 Announce Type: new Abstract: Reliable perception is essential for underwater vehicles operating in complex environments, where light attenuation and scattering often degrade visibil

On attention heads and bilinear forms

arXiv:2609.22990v1 Announce Type: new Abstract: We study the symmetric and antisymmetric parts of bilinear forms in the attention heads of trained large language models. We introduce an orthogonally i

On Emergent Capabilities and Model Merging

arXiv:2609.24504v1 Announce Type: new Abstract: Fine-tuned checkpoints and adapters now fill public repositories, and the most common operation applied to these artifacts is model merging: arithmetic

On Generalized Naive Bayes with Continuous Features

arXiv:2609.23819v1 Announce Type: cross Abstract: The Generalized Naive Bayes (GNB) model was introduced for discrete and categorical random variables as an extension of classic Naive Bayes. We now ac

On Learning Spatial Structure from Pre-Beamforming Per-Antenna Range-Doppler Radar Measurements

arXiv:2604.01921v2 Announce Type: replace Abstract: Automotive radar perception pipelines commonly construct angle-domain representations via beamforming before applying learning-based models. This wo

On The Robustness-Resolution Tradeoff In Temporal Quantization Of Event Streams

arXiv:2609.22295v1 Announce Type: new Abstract: Event pipelines often discretize asynchronous timestamps before learning. This step looks harmless, but its stability depends directly on temporal resol

One Patch, Three Roles: What Is Actually Coupled in Autoregressive Time-Series Forecasting?

arXiv:2609.23686v1 Announce Type: new Abstract: Patch-based autoregressive time-series forecasting often ties input representation, learned transitions, and recursive execution to one patch length. We

OnlineWM: Causality-Aware Active Online Learning for Effective World Modeling

arXiv:2609.23753v1 Announce Type: new Abstract: Generative world models aim to predict future states conditioned on actions, where action controllability is fundamental for reliable dynamics modeling.

OpenFlyScan: A Quality-Guided Aerial Reconstruction System for Consumer Drones

arXiv:2609.24253v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) provides high-fidelity scenes for large-scale embodied simulation, but constructing large-scale urban assets remains cons

Optimal Symmetries in Binary Classification

arXiv:2408.08823v2 Announce Type: replace Abstract: We develop a theoretical foundation for designing group-equivariant neural networks that align the choice of symmetries with the underlying probabil

Orientation-Aware Control and Trajectory Design for Aerial RIS-Assisted Wireless Communications

arXiv:2609.23157v1 Announce Type: cross Abstract: Aerial Reconfigurable Intelligent Surfaces (ARISs) can enhance wireless connectivity in obstructed environments by combining reconfigurable metasurfac

P2Flow: Phoneme-aware Progressive Flow Matching for Extreme Speech Super-Resolution

arXiv:2609.24138v1 Announce Type: cross Abstract: Generative models have recently demonstrated considerable promise in speech super-resolution (SSR). Nevertheless, the majority of existing work has co

PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Models

arXiv:2609.23574v1 Announce Type: cross Abstract: In high-dimensional tabular learning, feature screening provides a lightweight, model-agnostic way to remove irrelevant features before model fitting.

PanoSeg3R: Feed-Forward 3D Semantic Segmentation for Panoramic Images with an Automatic Data Curation Pipeline

arXiv:2609.22687v1 Announce Type: new Abstract: We present PanoSeg3R, a feed-forward framework for 3D panoramic semantic segmentation. Unlike existing methods designed for perspective inputs, PanoSeg3

Paragraph Boundaries Are Not White Space:Compression Depth as the Signature of Hierarchical Structure

arXiv:2609.23551v1 Announce Type: new Abstract: Standard positional encodings represent position as a one-dimensional reading-order coordinate, but reading order alone does not determine hierarchical

Partial-Scan-and-Move Source Seeking for Mobile Robots

arXiv:2609.23786v1 Announce Type: cross Abstract: This paper presents a partial-scan-and-move strategy for source seeking with a mobile robot equipped with an offset scalar sensor. At each robot posit

Patch-to-Global: Random Patch Diffusion for Globally Consistent Megapixel Artifact Inpainting in Whole Slide Images

arXiv:2609.24116v1 Announce Type: new Abstract: Although deep learning has advanced Whole Slide Image (WSI) Analysis, tissue artifacts like bubbles and folds often cause silent failures by concealing

Pay More Attention To Text In High-Resolution MLLMs

arXiv:2609.23495v1 Announce Type: new Abstract: Failures of high-resolution MLLMs are commonly attributed to a visual problem, motivating zooming, cropping, and related visual interventions to recover

Per-Query Gating of LLM Rerankers for Multi-Hop Retrieval

arXiv:2609.22880v1 Announce Type: cross Abstract: LLM rerankers add of the order of $0.2-0.3 per 1,000 queries and about a second of tail latency on top of a graph-augmented dense pipeline such as Hip

Physics-Informed Classical and Quantum Neural Networks for One-Dimensional Schrodinger Eigenvalue Problems

arXiv:2609.22189v1 Announce Type: cross Abstract: The Schrodinger equation in one spatial dimension admits a small set of exactly solvable potentials that serve as natural proving grounds for any new

Physics-residual machine learning predicts oxygen-evolution catalyst activity beyond the training range from sparse polarization measurements

arXiv:2609.23549v1 Announce Type: new Abstract: Screening oxygen-evolution catalysts on combinatorial libraries requires deciding which candidates receive the remaining measurements. The deciding acti

Poisson Exchange Beyond Submodularity: Effective Approximation Algorithms for Offline and Online Subset Selection over Matroids

arXiv:2609.24569v1 Announce Type: cross Abstract: Over the past decade, a growing body of research has shown that gamma-weak submodularity broadly arises in numerous subset selection tasks, including

Predicting magnetism with first-principles AI

arXiv:2602.09093v2 Announce Type: replace-cross Abstract: Computational discovery of magnetic materials remains challenging because magnetism arises from the competition between kinetic energy and Cou

Predicting Out-of-Distribution Generalization of Neural Operators via Observable Spectral Error Decomposition

arXiv:2609.23529v1 Announce Type: new Abstract: Neural operators have emerged as powerful surrogates for solving partial differential equations (PDEs), yet their reliability under distribution shift r

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma by Integrating Multimodal Ultrasound and Clinical Data: A Multicenter Study

arXiv:2609.24524v1 Announce Type: new Abstract: Background: Microvascular invasion (MVI) predicts recurrence and survival in hepatocellular carcinoma (HCC) but requires postoperative histopathology fo

Prescribed-Time Contracting-Boundary Control of a Tendon-Driven Flexible Arm

arXiv:2609.22963v1 Announce Type: new Abstract: This study develops a prescribed-time performance-shaping control method for curvature tracking of a single-segment flexible arm actuated by three antag

Pretrained Persona Mixture Models and Tandem Models for Human Simulation

arXiv:2609.22607v1 Announce Type: new Abstract: We argue here that the current dominant practice in LLM human simulation: prompting instruction-tuned assistant language models to role-play personas, i

Probabilistic Modelling of Operational Design Domains, A New Approach for Testing AI Systems

arXiv:2609.24397v1 Announce Type: new Abstract: The conventional testing process quickly fails when applied to ML-based systems such as obstacle detection in vehicles: if an obstacle is not detected i

ProxyBuild: Text-Guided Structured 3D Building Generation with Mesh-Anchored Procedural Proxies

arXiv:2609.23386v1 Announce Type: new Abstract: Text-guided 3D building generation holds tremendous application potential, yet existing generative models typically output inseparable single meshes or

PRQuant: Permutation Residual Quantization for Low-Overhead Inference

arXiv:2609.22106v1 Announce Type: cross Abstract: Accuracy of Low-bit quantization of linear layers is often dominated by a small number of outliers. Although existing methods, such as smoothing, rota

Q-TIE: A Lightweight and Generalizable Re-ranking Framework for Temporal Information Retrieval

arXiv:2609.23880v1 Announce Type: new Abstract: Temporal Information Retrieval (TIR) has been increasingly critical given the rise of Retrieval-Augmented Generation (RAG). Since temporally mismatched

QwenVLConnector: A Fast, Unified Medical VLM Chatbot for Fine-Grained Clinical Perception and Text Generation

arXiv:2609.23139v1 Announce Type: new Abstract: Most medical vision-language models (VLMs) excel at open-ended report generation and VQA but provide limited support for structured, fine-grained clinic

Rank Portability Does Not Imply Feasibility Portability: Target-Specific Evaluation of Joint Hardware Constraints

arXiv:2609.22122v1 Announce Type: new Abstract: Cross-device hardware evaluation often assumes that if architecture rankings transfer across devices, a proxy device can support target-side model selec

Read-Best Is Not Steer-Best: A Probing--Steering Layer Dissociation in Omni-Modal Large Language Models

arXiv:2609.22135v1 Announce Type: new Abstract: Omni-modal large language models integrate text, audio, and image signals into a shared residual stream, where concepts such as emotion can be linearly

Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network

arXiv:2607.14293v2 Announce Type: replace-cross Abstract: Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge ju

Real-Time Plasma State Prediction via FPGA-Accelerated Quantized Recurrent Probabilistic Neural Networks

arXiv:2609.23141v1 Announce Type: cross Abstract: Real time plasma state estimation for control of Tokamak devices are challenging due to the stringent latency requirements of the plasma control syste

RefAM: Attention Magnets for Zero-Shot Referral Segmentation

arXiv:2509.22650v3 Announce Type: replace Abstract: Most existing approaches to referring segmentation achieve strong performance only through fine-tuning or by composing multiple pre-trained models,

Reforge: Low-Latency Distributed GNN Serving with Selective Embedding Recomputation

arXiv:2501.08547v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have been widely adopted for their ability to compute expressive node representations in graph datasets. However,

Reinforcement Learning in Operational Research: A Technical Review and Practical Roadmap

arXiv:2609.24750v1 Announce Type: cross Abstract: The growing demand for real-time, data-driven decision-making in complex and dynamic systems is placing increasing pressure on traditional Operational

Relightable 3D Avatar Reconstruction with Semantic-Adaptive Motion-Illumination Responses

arXiv:2609.24158v1 Announce Type: new Abstract: Reconstructing expressive and relightable 3D head avatars from monocular videos remains challenging in computer vision, as it requires accurate modeling