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GRADE: Benchmarking Discipline-Informed Reasoning in Image Editing

arXiv:2603.12264v2 Announce Type: replace Abstract: Unified multimodal models target joint understanding, reasoning, and generation, but current image editing benchmarks are largely confined to natura

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GraLoD: Graphics-Inspired Continuous Level-of-Detail Learning for Image Restoration

DGX agent

arXiv:2609.16578v1 Announce Type: new Abstract: The spatial support required for image restoration varies across degradation types, image regions, and reconstruction stages. However, most existing met

researcharxiv-cs-cv

16 Sept 2026

GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning

arXiv:2509.23616v2 Announce Type: replace-cross Abstract: The class imbalance problem refers to the disproportionate distribution of samples across different classes within a dataset, where the minori

Agents

Grounding SWE-Agent Decisions in Architecture-0 Design: Navigating Unknown Unknowns through Physical Mapping

arXiv:2609.17221v1 Announce Type: cross Abstract: Autonomous Software Engineering Agents (SWE-Agents) excel in deterministic coding tasks but struggle with Architecture 0, the nascent system design ph

agentsarxiv-cs-ai

GrowMTP: Can RL Grow Its Own Draft Head?

arXiv:2609.16648v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training drives the frontier capabilities of large language models, with its wall-clock dominated by autoregressive r

safetyarxiv-cs-cl

Applications

HairCS: Reconstructing Strand-Based Hair from Hair Cards

arXiv:2609.16465v1 Announce Type: cross Abstract: We present an automated pipeline that converts hair-card models into high-quality strand-based hairstyles. Given a collection of textured triangular o

applicationsarxiv-cs-cv

Hamilton-Jacobi Reachability for Hybrid Systems: Unified Goal-Driven Control with Safety Guarantees

arXiv:2609.17430v1 Announce Type: new Abstract: Hybrid dynamical systems provide a powerful modeling framework for robotic systems, particularly in contact-rich environments. However, ensuring safety

safetyarxiv-cs-ro

High-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning with Applications in Fluid Dynamics

arXiv:2609.17101v1 Announce Type: new Abstract: The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e.,

Tutorials

High-Fidelity Video Quality Assessment with VQA-Specific Saliency

arXiv:2609.16946v1 Announce Type: new Abstract: No-reference video quality assessment (NR VQA) has recently seen promising progress with deep learning. However, video data is inherently large, and pro

tutorialsarxiv-cs-cv

Hardware

High-Performance Tensor Formulation of the Viterbi Algorithm for Hidden Semi-Markov Models

arXiv:2609.16500v1 Announce Type: new Abstract: Hidden Semi-Markov Models (HSMMs) are fundamental probabilistic models widely adopted across diverse domains, from computational biology to finance and

hardwarearxiv-cs-lg

HintMiner: Automatic Question Hints Mining From Q&A Web Posts with Language Model via Self-Supervised Learning

arXiv:2609.16060v1 Announce Type: cross Abstract: Users often need ask questions and seek answers online. The Question - Answering (QA) forums such as Stack Overflow cannot always respond to the quest

HLC-GS: Risk-Map-Guided Height-Layer Consistency Gaussian Splatting for DSM Reconstruction from Optical Satellite Imagery

arXiv:2609.16772v1 Announce Type: new Abstract: A Digital Surface Model (DSM) is a fundamental geospatial data product for representing the elevation of the Earth's surface. Recently, 3D Gaussian Spla

researcharxiv-cs-cv

Tutorials

How Clinicians Think and What AI Can Learn From It

arXiv:2601.12547v2 Announce Type: replace Abstract: Clinical artificial intelligence increasingly builds high-dimensional representations of patients, yet every finite clinical model is an abstraction

tutorialsarxiv-cs-ai

How Good Are Time-Series Foundation Models for Pedestrian Crowd Count Forecasting? A Cross-Dataset Comparative Study

model-releasesarxiv-cs-ai

arXiv:2609.16415v1 Announce Type: cross Abstract: Pedestrian-count forecasting supports pedestrian-oriented Intelligent Transportation Systems (ITS), including crowd monitoring, pedestrian-traffic sta

How Humans and LLMs Read Gender into Gender-Neutral Physical Descriptions

arXiv:2609.16366v1 Announce Type: cross Abstract: When foundation models describe people, recent work in AI fairness, accessibility, and ethics recommends avoiding inferred identity labels (e.g., 'she

safetyarxiv-cs-ai

Applications

How I learned to stop worrying and love StopGrads: Stationarity, Convergence, and a case study on Flow Map Learning

arXiv:2609.16222v1 Announce Type: new Abstract: Stopgrads are widely used in training machine learning models, but stopgrads can alter the gradient, stationary points and convergence guarantees of the

applicationsarxiv-cs-lg

Hub-Spectral Activation of Latent Multimodal Knowledge

arXiv:2609.17094v1 Announce Type: new Abstract: Multimodal representation learning seeks shared representations for cross-modal retrieval and knowledge transfer. Hub-based binding reduces pairwise sup

safetyarxiv-cs-cv

HUMAID-NER: A Disaster Tweet Dataset for Joint Named Entity Recognition and Event Classification via Uncertainty-Weighted Multitask Learning

model-releasesarxiv-cs-cl

arXiv:2609.16964v1 Announce Type: new Abstract: Rapid extraction of structured information from social media is important for humanitarian response, yet existing disaster tweet resources mainly provid

HuMemSLAM: Efficient Human-Inspired Semantic Place Recognition for Robust Visual SLAM

arXiv:2609.17168v1 Announce Type: cross Abstract: Autonomous systems require reliable place recognition for efficient and effective simultaneous localisation and mapping (SLAM). Traditional geometric

Hybrid Variational Quantum Circuits for Multivariate Regression and High-Dimensional Data Reconstruction

model-releasesarxiv-cs-lg

arXiv:2609.17358v1 Announce Type: new Abstract: Variational quantum circuits (VQCs) are parameterized quantum circuits optimized classically. We propose a hybrid variational quantum circuit (HVQC) ext

HyCoSeq: Contextual Hyperbolic Representation Learning for Genomic Sequences

arXiv:2609.16925v1 Announce Type: new Abstract: Hyperbolic geometry provides a natural inductive bias for genomic representation learning, but existing hyperbolic genomic models primarily use Lorentz

safetyarxiv-cs-lg

Hyper-RED: Scalable Event Pre-training via Semantic Hypergraph Distillation

arXiv:2609.16811v1 Announce Type: new Abstract: Event cameras have shown great potential for robust visual perception, yet scaling event representation learning remains challenging due to the scarcity

safetyarxiv-cs-cv

Hyperbolic Contrastive Learning with Entailment for Spatial Transcriptomics

arXiv:2609.16207v1 Announce Type: new Abstract: Spatial Transcriptomics (ST) has transformed biomedical research by enabling the spatial mapping of gene expression across tissue sections. However, hig

researcharxiv-cs-cv

IL-ACT: Imitation Learning with Adaptive Cartesian Tracking Control for a 30-ton Excavator

arXiv:2609.16696v1 Announce Type: new Abstract: Autonomous excavator control is challenged by coupled kinematics, actuation lag, and uncertainty. We propose imitation learning and adaptive Cartesian t

safetyarxiv-cs-ro

Implementing a White-Box Undetectable Backdoor for Random Fourier Features

arXiv:2609.16403v1 Announce Type: cross Abstract: Goldwasser et al. showed that undetectable backdoors can be planted in machine learning models trained with the Random Fourier Features (RFF) algorith

ImpossibleRubrics: Stress-Testing Generated Rubrics as Reward Signals

model-releasesarxiv-cs-cl

arXiv:2609.16816v1 Announce Type: cross Abstract: Language model-generated rubrics are increasingly used as reward signals for rubric-based reinforcement learning, LLM-as-a-judge evaluation, and autom

Improving Reduced-Order Rotating Detonation Engine Models with Data Assimilation and Machine Learning

arXiv:2609.16237v1 Announce Type: cross Abstract: Rotating detonation engines (RDEs) exhibit strongly nonlinear, multiscale wave dynamics that set the observed thermal field. High-fidelity simulations

IMVS: Interactive Medical Volume Segmentation with Test-Time Adaptation - A New Method for Annotating Radiology Datasets

arXiv:2609.16775v1 Announce Type: new Abstract: Annotating large radiology datasets is bottlenecked by the manual effort of delineating structures slice-by-slice in 3D volumes. Interactive methods red

safetyarxiv-cs-cv

Information Geometric Self-Organization at the Edge of Stability in High-Capacity Kernel Associative Memories

model-releasesarxiv-cs-lg

arXiv:2609.16827v1 Announce Type: new Abstract: High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit exceptional storage capabilities and robustness. Previous empirical

InfoTaxa: Information-Calibrated Label-Free Clustering for Fine-Grained Visual Taxonomy

arXiv:2609.17218v1 Announce Type: new Abstract: Label-free clustering of frozen pretrained visual embeddings offers a scalable route to biodiversity monitoring, but image-only fine-grained taxonomy ex

researcharxiv-cs-cv

Integrating the Analytic Hierarchy Process with Large Language Models for Transparent Multi-Criteria Decision-Making

model-releasesarxiv-cs-ai

arXiv:2609.16779v1 Announce Type: new Abstract: LLMs are increasingly employed in a wide range of decision-making tasks. However, the opacity of their internal reasoning makes it difficult to validate

Intelligent Interaction Techniques (IIxT) - Proposal

arXiv:2609.16295v1 Announce Type: cross Abstract: Interaction techniques (IxTs) are the low-level, reusable components out of which user interfaces are designed, including menus, scroll bars, text inp

Interactive Memory Learning for Long-Term Conversations

arXiv:2609.17088v1 Announce Type: new Abstract: Recent advancements in large language models have significantly enhanced the capabilities of agents in modeling long-term conversations. Despite these s

safetyarxiv-cs-ai

Interpreting and Steering LLM Agents for Social Simulations

arXiv:2609.16436v1 Announce Type: cross Abstract: Simulations based on large language models (LLMs) have proven to be powerful for understanding human behavior, making them valuable additions to the s

Agents

Intrinsic Motivation in Reinforcement Learning: A Research Agenda for Adaptive Self-Organisation

arXiv:2609.17325v1 Announce Type: new Abstract: Biological cells can be viewed as individual, interacting agents whose collective dynamics give rise to adaptive behaviour at multiple levels of organis

agentsarxiv-cs-ai

Intrinsic Robot Rewarding: Reusing VLA Representations for Autonomous Evaluation and Policy Improvement

arXiv:2609.17115v1 Announce Type: cross Abstract: Vision-language-action (VLA) systems already bring together two valuable resources for robot learning: rich visual representations and demonstrations

safetyarxiv-cs-lg

IRENE: A Convolutional GRU Ensemble Model for Radar Precipitation Nowcasting over Italy

arXiv:2609.17175v1 Announce Type: new Abstract: We present IRENE (Italian Radar Ensemble Nowcasting Experiment), a deep learning model for probabilistic short-range precipitation nowcasting over the I

Hardware

Is INT8 Portable? A Cross-Platform Measurement Study of Quantized Inference on Embedded and Automotive Accelerators

arXiv:2609.16085v1 Announce Type: cross Abstract: Eight-bit integer (INT8) post-training quantization is the default recipe for edge deployment, under a widely held assumption: INT8 makes inference fa

hardwarearxiv-cs-lg

ISS Policy : Scalable Diffusion Policy with Implicit Scene Supervision

model-releasesarxiv-cs-ro

arXiv:2512.15020v3 Announce Type: replace Abstract: Vision-based imitation learning has enabled impressive robotic manipulation skills, but action imitation alone provides limited supervision of the g

Japanese Stroke LLM Evaluation: A Conversational Benchmark for Safe Stroke Care in Japanese Using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.16739v1 Announce Type: new Abstract: Background: Large language models (LLMs) have achieved physician-comparable performance on multiple-choice medical knowledge examinations, but their cap

JewelTry: Mask-Free Scale Aware Jewelry Virtual Try-On

arXiv:2609.16626v1 Announce Type: new Abstract: Virtual try-on (VTON) enables customers to visualize how fashion products appear when worn and has become an important technology for online shopping. W

Local Ai

JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management

arXiv:2609.17475v1 Announce Type: new Abstract: Capable open-weight models make local coding and reasoning attractive, but their context and execution state strain laptop memory. We present JustFit, a

local-aiarxiv-cs-ai

Agents

Kernel-Based Metrics Learning for Uncertain Opponent Vehicle Trajectory Prediction in Autonomous Racing

arXiv:2609.17147v1 Announce Type: cross Abstract: Autonomous racing confronts significant challenges in safely overtaking Opponent Vehicles (OVs) that exhibit uncertain trajectories, stemming from unk

agentsarxiv-cs-ai

Knowledge as Orbit: Finite Collections as Phases of an Exactly Periodic Latent Generator

arXiv:2609.17417v1 Announce Type: cross Abstract: Finite knowledge is usually stored extensionally, one code or vector per item. We ask whether a finite collection can instead be stored intensionally,

LACE: Layer-Wise Compression for Dynamic Frame Rate Codecs

model-releasesarxiv-cs-ai

arXiv:2609.17509v1 Announce Type: cross Abstract: Neural audio codecs are a key component in speech language modeling. However, their high frame rates lead to long sequence lengths, increasing computa

Language Orthogonalization for Zero-Shot Cross-Lingual Audio Deepfake Detection

arXiv:2609.16458v1 Announce Type: cross Abstract: Audio deepfake detectors need to transfer to languages absent from training, as multilingual speech synthesis outpaces labeled anti-spoofing resources

researcharxiv-cs-cl

Applications

Large Language Models Develop Belief State Geometry In-Context

arXiv:2609.17376v1 Announce Type: cross Abstract: Large language models (LLMs) trained on next-token prediction exhibit remarkable in-context learning (ICL) abilities, yet the representations that sup

applicationsarxiv-cs-cl

Large Language Models in the Loop: A Stability- and Network-Aware Survey in Networked Control, Cyber-Physical, and Multi-Agent Systems

arXiv:2609.16599v1 Announce Type: cross Abstract: Modern networked control systems (NCSs), cyber-physical systems (CPSs), and complex multi-agent network systems (CNSs) increasingly rely on large lang

safetyarxiv-cs-ai