Search: “benchmark”

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

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

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Hardware

Flow Augmentation and Knowledge Distillation for Lightweight Face Presentation Attack Detection

DGX agent

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

14 May 2026

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

safetyarxiv-cs-lg

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

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

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

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

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

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

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

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

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

HADAR-Based Thermal Infrared Hyperspectral Image Restoration

arXiv:2605.13664v1 Announce Type: new Abstract: Thermal-infrared (TIR) hyperspectral imagery (HSI) provides critical scene information for various applications. However, its practical utility is sever

HarmoGS: Robust 3D Gaussian Splatting in the Wild via Conflict-Aware Gradient Harmonization

arXiv:2605.13073v1 Announce Type: new Abstract: In-the-wild 3D Gaussian Splatting remains challenging due to transient distractors and illumination-induced cross-view appearance inconsistencies. Exist

researcharxiv-cs-cv

Harnessing Agentic Evolution

arXiv:2605.13821v1 Announce Type: new Abstract: Agentic evolution has emerged as a powerful paradigm for improving programs, workflows, and scientific solutions by iteratively generating candidates, e

agentsarxiv-cs-ai

// Harnessing Agentic Evolution // Pay attention to this one if you run iterative agentic search loops. (bookmark it) AEvo splits the self-i…

// Harnessing Agentic Evolution // Pay attention to this one if you run iterative agentic search loops. (bookmark it) AEvo splits the self-improvement loop into two jobs: > One proposes the next candi

agentsdair-ai--x

HCSG: Human-Centric Semantic-Geometric Reasoning for Vision-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2605.13321v1 Announce Type: new Abstract: VLN has achieved remarkable progress by scaling data and model capacity. However, the assumption of a static environment breaks down in real-world indoo

Hessian Matching for Machine-Learned Coarse-Grained Molecular Dynamics

arXiv:2605.12823v1 Announce Type: new Abstract: Coarse-grained (CG) molecular dynamics enables simulations of atomic systems such as biomolecules at timescales inaccessible to all-atom (AA) methods, b

Hierarchical Attacks for Multi-Modal Multi-Agent Reasoning

arXiv:2605.13213v1 Announce Type: new Abstract: Multi-modal multi-agent systems (MM-MAS) have gained increasing attention for their capacity to enable complex reasoning and coordination across diverse

Hierarchical Transformer Preconditioning for Interactive Physics Simulation

arXiv:2605.13343v1 Announce Type: cross Abstract: Neural preconditioners for real-time physics simulation offer promising data-driven priors, but they often fail to capture long-range couplings effici

ImageAttributionBench: How Far Are We from Generalizable Attribution?

arXiv:2605.12967v1 Announce Type: new Abstract: The rapid advancement of generative AI has enabled the creation of highly realistic and diverse synthetic images, posing critical challenges for image p

Implicit Behavioral Decoding from Next-Step Spike Forecasts at Population Scale

arXiv:2605.12999v1 Announce Type: cross Abstract: Closed-loop brain-computer interfaces often require both a forecast of upcoming neural population activity and a readout of the animal's behavioral st

Imposing Boundary Conditions on Neural Operators via Learned Function Extensions

arXiv:2602.04923v2 Announce Type: replace Abstract: Neural operators have emerged as powerful surrogates for the solution of partial differential equations (PDEs), yet their ability to handle general,

Improving Classifier-Free Guidance of Flow Matching via Manifold Projection

arXiv:2601.21892v2 Announce Type: replace-cross Abstract: Classifier-free guidance (CFG) is a widely used technique for controllable generation in diffusion and flow-based models. Despite its empirica

safetyarxiv-cs-ai

Inducing Overthink: Hierarchical Genetic Algorithm-based DoS Attack on Black-Box Large Language Reasoning Models

arXiv:2605.13338v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) are increasingly integrated into systems requiring reliable multi-step inference, yet this growing dependence exposes ne

KamonBench: A Grammar-Based Dataset for Evaluating Compositional Factor Recovery in Vision-Language Models

arXiv:2605.13322v1 Announce Type: new Abstract: Kamon (family crests) are an important part of Japanese culture and a natural test case for compositional visual recognition: each crest combines a smal

Learning Responsibility-Attributed Adversarial Scenarios for Testing Autonomous Vehicles

model-releasesarxiv-cs-ro

arXiv:2605.13751v1 Announce Type: new Abstract: Establishing trustworthy safety assurance for autonomous driving systems (ADSs) requires evidence that failures arise from avoidable system deficiencies

Local Ai

Learning to See What You Need: Gaze Attention for Multimodal Large Language Models

arXiv:2605.13080v1 Announce Type: new Abstract: When humans describe a visual scene, they do not process the entire image uniformly; instead, they selectively fixate on regions relevant to their inten

local-aiarxiv-cs-cv

LIFT: Last-Mile Fine-Tuning for Table Explicitation

arXiv:2605.13424v1 Announce Type: new Abstract: We propose last-mile fine-tuning, or Lift, a pipeline in which a pre-trained large language model extracts an initial table from unstructured clipboard

LightSplit: Practical Privacy-Preserving Split Learning via Orthogonal Projections

arXiv:2605.13265v1 Announce Type: new Abstract: Split learning (SL) enables collaborative training by partitioning a neural network across clients and a central server, but the cut-layer interface int

researcharxiv-cs-lg

LLMs as annotators of credibility assessment in Danish asylum decisions: evaluating classification performance and errors beyond aggregated metrics

arXiv:2605.13412v1 Announce Type: cross Abstract: Off-the-shelf large language models (LLMs) are increasingly used to automate text annotation, yet their effectiveness remains underexplored for underr

Loopholing Discrete Diffusion: Deterministic Bypass of the Sampling Wall

arXiv:2510.19304v3 Announce Type: replace Abstract: Discrete diffusion models offer a promising alternative to autoregressive generation through parallel decoding, but they suffer from a sampling wall

researcharxiv-cs-lg

LoRA-Mixer: Coordinate Modular LoRA Experts Through Serial Attention Routing

arXiv:2507.00029v2 Announce Type: replace-cross Abstract: Recent attempts to combine low-rank adaptation (LoRA) with mixture-of-experts (MoE) for multi-task adaptation of Large Language Models (LLMs)

Low-Rank Adapters Initialization via Gradient Surgery for Continual Learning

arXiv:2605.12752v1 Announce Type: new Abstract: LoRA is widely adopted for continual fine-tuning of Large Language Models due to its parameter efficiency, modularity across tasks, and compatibility wi

M2Retinexformer: Multi-Modal Retinexformer for Low-Light Image Enhancement

arXiv:2605.12556v1 Announce Type: new Abstract: Low-light image enhancement is challenging due to complex degradations, including amplified noise, artifacts, and color distortion. While Retinex-based

researcharxiv-cs-cv

MambaPanoptic: A Vision Mamba-based Structured State Space Framework for Panoptic Segmentation

arXiv:2605.12640v1 Announce Type: new Abstract: Panoptic segmentation requires the simultaneous recognition of countable thing instances and amorphous stuff regions, placing joint demands on long-rang

researcharxiv-cs-cv

MAP: A Map-then-Act Paradigm for Long-Horizon Interactive Agent Reasoning

arXiv:2605.13037v1 Announce Type: new Abstract: Current interactive LLM agents rely on goal-conditioned stepwise planning, where environmental understanding is acquired reactively during execution rat

agentsarxiv-cs-ai

McCast: Memory-Guided Latent Drift Correction for Long-Horizon Precipitation Nowcasting

arXiv:2605.13197v1 Announce Type: cross Abstract: Existing precipitation nowcasting methods typically adopt an autoregressive formulation, where future states are predicted from previous outputs. Howe

MedCore: Boundary-Preserving Medical Core Pruning for MedSAM

arXiv:2605.13688v1 Announce Type: new Abstract: Medical segmentation foundation models such as SAM and MedSAM provide strong prompt-driven segmentation, but their image encoders are still too large fo

MindVLA-U1: VLA Beats VA with Unified Streaming Architecture for Autonomous Driving

arXiv:2605.12624v1 Announce Type: cross Abstract: Autonomous driving has progressed from modular pipelines toward end-to-end unification, and Vision-Language-Action (VLA) models are a natural extensio

MLGIB: Multi-Label Graph Information Bottleneck for Expressive and Robust Message Passing

arXiv:2605.13126v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) suffer from over-squashing in deep message passing, where information from exponentially growing neighborhoods is compres

MMSkills: Towards Multimodal Skills for General Visual Agents

arXiv:2605.13527v1 Announce Type: new Abstract: Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as te

agentsarxiv-cs-ai

Local Ai

MorphOPC: Advancing Mask Optimization with Multi-scale Hierarchical Morphological Learning

arXiv:2605.12528v1 Announce Type: cross Abstract: As feature sizes shrink to the nanometer scale, accurately transferring circuit patterns from photomasks to silicon wafers becomes increasingly challe

local-aiarxiv-cs-ai

Tutorials

Multi-Modal Guided Multi-Source Domain Adaptation for Object Detection

arXiv:2605.13140v1 Announce Type: new Abstract: General object detection (OD) struggles to detect objects in the target domain that differ from the training distribution. To address this, recent studi

tutorialsarxiv-cs-cv

Multi-Modal World Model for Physical Robot Interactions: Simultaneous Visual and Tactile Predictions for Enhanced Accuracy

arXiv:2304.11193v2 Announce Type: replace-cross Abstract: Predicting the outcomes of robotic actions, often referred to as learning a world model, in complex environments remains a fundamental challen

Multi-Rollout On-Policy Distillation via Peer Successes and Failures

arXiv:2605.12652v1 Announce Type: cross Abstract: Large language models are often post-trained with sparse verifier rewards, which indicate whether a sampled trajectory succeeds but provide limited gu

safetyarxiv-cs-ai

Neurosymbolic Auditing of Natural-Language Software Requirements

arXiv:2605.13817v1 Announce Type: cross Abstract: Natural-language software requirements are often ambiguous, inconsistent, and underspecified; in safety-critical domains, these defects propagate into

NFR: Neural Feature-Guided Non-Rigid Shape Registration

arXiv:2505.22445v2 Announce Type: replace-cross Abstract: In this paper, we propose a novel learning-based framework for 3D shape registration, which overcomes the challenges of significant non-rigid