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Few-Shot Physics-Informed Neural Network for Shape Reconstruction of Concentric-Tube Robots

model-releasesarxiv-cs-ro

arXiv:2605.12790v1 Announce Type: new Abstract: Modeling concentric tube robots (CTRs) involves complex nonlinear continuum mechanics, and despite recent progress, physics-based models often lack an a

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Agents

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition

DGX agent

arXiv:2605.13193v1 Announce Type: new Abstract: Fine-grained recognition in everyday life is often not a closed-book classification problem: when encountering unfamiliar objects, humans actively searc

agentsarxiv-cs-cv

14 May 2026

Filter-then-Weight: Online Data Selection and Reweighting for LLM Fine-Tuning

arXiv:2604.00001v2 Announce Type: replace-cross Abstract: Gradient-based data selection offers a principled framework for estimating sample utility in large language model (LLM) fine-tuning, but exist

Agents

Finding the Weakest Link: Adversarial Attack against Multi-Agent Communications

arXiv:2605.13170v1 Announce Type: new Abstract: Multi-agent systems rely on communication for information sharing and action coordination, which exposes a vulnerability to attacks. We investigate sing

agentsarxiv-cs-lg

Hardware

FlashSampling: Fast and Memory-Efficient Exact Sampling

arXiv:2603.15854v2 Announce Type: replace-cross Abstract: Sampling from a categorical distribution is mathematically simple, but in large-vocabulary decoding, it often triggers extra memory traffic an

hardwarearxiv-cs-ai

Hardware

Flow Augmentation and Knowledge Distillation for Lightweight Face Presentation Attack Detection

arXiv:2605.13108v1 Announce Type: new Abstract: Face presentation attack detection (FacePAD) remains challenging under diverse spoofing representation, including 2D print and replay, 3D mask-based spo

hardwarearxiv-cs-cv

Flow Matching for Offline Reinforcement Learning with Discrete Actions

arXiv:2602.06138v2 Announce Type: replace Abstract: Generative policies based on diffusion models and flow matching have shown strong promise for offline reinforcement learning (RL), but their applica

Flow Matching with Uncertainty Quantification and Guidance

arXiv:2602.10326v2 Announce Type: replace Abstract: Despite the remarkable success of sampling-based generative models such as flow matching, they can still produce samples of inconsistent or degraded

researcharxiv-cs-cv

Applications

FMC-DETR: Frequency-Decoupled Multi-Domain Coordination for Aerial-View Object Detection

arXiv:2509.23056v2 Announce Type: replace Abstract: Remote sensing object detection is a critical technology for real-world applications such as natural resource monitoring, traffic management, and UA

applicationsarxiv-cs-cv

FOAM: Blocked State Folding for Memory-Efficient LLM Training

arXiv:2512.07112v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated remarkable performance due to their large parameter counts and extensive training data. However

Follow-Bench: A Unified Motion Planning Benchmark for Socially-Aware Robot Person Following

model-releasesarxiv-cs-ro

arXiv:2509.10796v4 Announce Type: replace Abstract: Robot person following (RPF) -- mobile robots that follow and assist a specific person -- has emerging applications in personal assistance, security

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs

arXiv:2605.13788v1 Announce Type: new Abstract: Active learning for machine-learning interatomic potentials (MLIPs) must address several challenges to be practical: scaling to large candidate pools, l

Formal Conjectures: An Open and Evolving Benchmark for Verified Discovery in Mathematics

arXiv:2605.13171v1 Announce Type: new Abstract: As automated reasoning systems advance rapidly, there is a growing need for research-level formal mathematical problems to accurately evaluate their cap

FRAME: Forensic Routing and Adaptive Multi-path Evidence Fusion for Image Manipulation Detection

arXiv:2605.12826v1 Announce Type: cross Abstract: The proliferation of sophisticated image editing tools and generative artificial intelligence models has made verifying the authenticity of digital im

FrameSkip: Learning from Fewer but More Informative Frames in VLA Training

arXiv:2605.13757v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are commonly trained from dense robot demonstration trajectories, often collected through teleoperation, by sampli

safetyarxiv-cs-ro

Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation

arXiv:2605.12997v1 Announce Type: new Abstract: Neural operators learn to map initial conditions to the terminal solution of partial differential equations (PDEs), providing a surrogate for the full o

From Baselines to Transport Geodesics: Axiomatic Attribution via Optimal Generative Flows

arXiv:2603.05093v2 Announce Type: replace-cross Abstract: Feature attributions often hide a critical modeling choice: they explain a prediction along a counterfactual path from a reference state to an

From Generalist to Specialist Representation

arXiv:2605.12733v1 Announce Type: cross Abstract: Given a generalist model, learning a task-relevant specialist representation is fundamental for downstream applications. Identifiability, the asymptot

From Heuristics to Analytics: Forecasting Effort and Progress in Online Learning

arXiv:2605.12788v1 Announce Type: new Abstract: Sustained effort is essential for realizing the benefits of intelligent tutoring systems (ITS), yet many learners disengage or underuse available practi

From Instance Selection to Fixed-Pool Data Recipe Search for Supervised Fine-Tuning

arXiv:2605.12944v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) data selection is commonly formulated as instance ranking: score each example and retain a top-k subset. However, effective

From Pixels to BFS: High Maze Accuracy Does Not Imply Visual Planning

arXiv:2603.26839v2 Announce Type: replace-cross Abstract: How do multimodal models solve visual spatial tasks -- through genuine planning, or through brute-force search in token space? We introduce ex

GAAMA: Graph Augmented Associative Memory for Agents

arXiv:2603.27910v2 Announce Type: replace Abstract: AI agents that interact with users across multiple sessions require persistent long-term memory to maintain coherent, personalized behavior. Current

GAGPO: Generalized Advantage Grouped Policy Optimization

arXiv:2605.13217v1 Announce Type: cross Abstract: Reinforcement learning has become a powerful paradigm for post-training large language model agents, yet credit assignment in multi-turn environments

Galilean State Estimation for Inertial Navigation Systems with Unknown Time Delay

model-releasesarxiv-cs-ro

arXiv:2605.13266v1 Announce Type: new Abstract: Many Inertial Navigation Systems (INS) use Global Navigation Satellite System (GNSS) position as the primary measurement to drive filter performance and

Local Ai

GenCape: Structure-Inductive Generative Modeling for Category-Agnostic Pose Estimation

arXiv:2605.13151v1 Announce Type: new Abstract: Category-agnostic pose estimation (CAPE) aims to localize keypoints on query images from arbitrary categories, using only a few annotated support exampl

local-aiarxiv-cs-cv

Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report

arXiv:2605.13555v1 Announce Type: cross Abstract: Radiation therapy (RT) requires precise dose delivery over multiple fractions, with CT fundamental for treatment planning due to its electron density

Generative Modeling by Minimizing the Wasserstein-2 Loss

arXiv:2406.13619v4 Announce Type: replace-cross Abstract: This paper develops a generative model by minimizing the second-order Wasserstein loss (the W_2 loss) through a distribution-dependent ordinar

Generative Modeling from Black-box Corruptions via Self-Consistent Stochastic Interpolants

arXiv:2512.10857v2 Announce Type: replace-cross Abstract: Transport-based methods have emerged as a leading paradigm for building generative models from large, clean datasets. However, in many scienti

Generative Modeling of Approximately Periodic Time Series by a Posterior-Weighted Gaussian Process

arXiv:2605.13150v1 Announce Type: cross Abstract: Discrete automated processes in industrial and cyber-physical systems often exhibit a repetitive structure in which successive repetitions follow a co

Generative Motion In-betweening by Diffusion over Continuous Implicit Representations

arXiv:2605.12778v1 Announce Type: cross Abstract: Recent advances in generative models have yielded impressive progress on motion in-betweening, allowing for more complex, varied, and realistic motion

researcharxiv-cs-cv

Generative Texture Diversification of 3D Pedestrians for Robust Autonomous Driving Perception

arXiv:2605.13755v1 Announce Type: new Abstract: In recent years, autonomous driving has significantly in creased the demand for high-quality data to train 2D and 3D perception models for safety-critic

safetyarxiv-cs-cv

GeoFlowVLM: Geometry-Aware Joint Uncertainty for Frozen Vision-Language Embedding

arXiv:2605.13352v1 Announce Type: new Abstract: Standard dual-encoder vision-language models that map images and text to deterministic points on a shared unit hypersphere through ell_2 normalization t

Hardware

Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later

arXiv:2509.19929v4 Announce Type: replace-cross Abstract: Uncertainty Quantification (UQ) is paramount for inference in engineering. A common inference task is to recover full-field information of phy

hardwarearxiv-cs-lg

Geometric Preconditioning and Curriculum Optimization for Trainable Variational Quantum Regression

arXiv:2601.11942v3 Announce Type: replace Abstract: Variational quantum circuits are increasingly studied as continuous-function approximators, but quantum regression remains difficult to train when g

GeomHair: Reconstruction of Hair Strands from Colorless 3D Scans

arXiv:2505.05376v3 Announce Type: replace Abstract: We propose a novel method that reconstructs hair strands directly from colorless 3D scans by leveraging multi-modal hair orientation extraction. Hai

GHGbench: A Unified Multi-Entity, Multi-Task Benchmark for Carbon Emission Prediction

arXiv:2605.13743v1 Announce Type: new Abstract: Open datasets and benchmarks for entity-level carbon-emission prediction remain fragmented across access, scale, granularity, and evaluation. We introdu

Local Ai

GLASS: Global-Local Aggregation for Inference-time Sparsification of LLMs

arXiv:2508.14302v2 Announce Type: replace-cross Abstract: Inference-time sparsification is a promising path to deploy large language models (LLMs) on resource-constrained devices, yet existing trainin

local-aiarxiv-cs-ai

GRACE: Gradient-aligned Reasoning Data Curation for Efficient Post-training

arXiv:2605.13130v1 Announce Type: new Abstract: Existing reasoning data curation pipelines score whole samples, treating every intermediate step as equally valuable. In reality, steps within a trace c

safetyarxiv-cs-ai

Gradual Domain Adaptation for Graph Learning

arXiv:2501.17443v4 Announce Type: replace Abstract: Existing machine learning literature lacks graph-based domain adaptation techniques capable of handling large distribution shifts, primarily due to

Graph-Based Financial Fraud Detection with Calibrated Risk Scoring and Structural Regularization

arXiv:2605.12782v1 Announce Type: new Abstract: Financial transaction fraud prevention faces challenges such as complex relationship structures, concealed behavioral patterns, and dynamically changing

Applications

Graph Neural Networks with Triangle-Based Messages for the Multicut Problem

arXiv:2605.13673v1 Announce Type: new Abstract: The multicut problem is an NP-hard combinatorial optimization problem with diverse applications in fields such as bioinformatics, data mining and comput

applicationsarxiv-cs-lg

GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?

arXiv:2605.12827v1 Announce Type: cross Abstract: Graph neural networks (GNNs) deployed as cloud services can be stolen through model-extraction attacks, which train a surrogate from query responses t

Tutorials

GraphThinker: Reinforcing Temporally Grounded Video Reasoning with Event Graph Thinking

arXiv:2602.17555v3 Announce Type: replace Abstract: Video reasoning requires a fine-grained understanding of the temporal dependencies and event-level relations between objects and events in videos. C

tutorialsarxiv-cs-cv

Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics

arXiv:2605.12728v1 Announce Type: cross Abstract: The power distribution engineering workforce faces a projected shortage of up to 1.5 million engineers by 2030, creating urgent demand for more access

Local Ai

GRIP-VLM: Group-Relative Importance Pruning for Efficient Vision-Language Models

arXiv:2605.13375v1 Announce Type: cross Abstract: In Vision-Language Models (VLMs), processing a massive number of visual tokens incurs prohibitive computational overhead. While recent training-aware

local-aiarxiv-cs-ai

Agents

GTA: Advancing Image-to-3D World Generation via Geometry Then Appearance Video Diffusion

arXiv:2605.12957v1 Announce Type: new Abstract: Recent developments in generative models and large-scale datasets have substantially advanced 3D world generation, facilitating a broad range of domains

agentsarxiv-cs-cv

GuardMarkGS: Unified Ownership Tracing and Edit Deterrence for 3D Gaussian Splatting

arXiv:2605.12919v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) is becoming a practical representation for novel view synthesis, but its growing adoption, together with rapid advances in

Guide, Think, Act: Interactive Embodied Reasoning in Vision-Language-Action Models

arXiv:2605.13632v1 Announce Type: cross Abstract: In this paper, we propose GTA-VLA(Guide, Think, Act), an interactive Vision-Language-Action (VLA) framework that enables spatially steerable embodied