Search: “benchmark”

Evaluating Vision Foundation Models for Pixel and Object Classification in Microscopy

arXiv:2603.19802v2 Announce Type: replace Abstract: Deep learning underlies most modern approaches and tools in computer vision, including biomedical imaging. However, for interactive semantic segment

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Model Releases

Exploratory, Communicative, and Deployable: Vision-Driven Embodied Agents for Open-World Mobile Manipulation

DGX agent

arXiv:2607.13653v1 Announce Type: new Abstract: Real-world deployment of embodied agents requires active exploration, visual grounding, and interactive intent disambiguation. However, existing framewo

model-releasesarxiv-cs-cv

16 Jul 2026

EXPLORE: Exploration with Guided Search for Analog Topology Generation using Language Models

arXiv:2607.13416v1 Announce Type: new Abstract: Automating analog circuit topology design is essential to reduce the extensive manual effort required to meet increasingly diverse and customized applic

EZSMT Version 3, Matured

arXiv:2607.13344v1 Announce Type: new Abstract: Constraint Answer Set Programming (CASP) is a hybrid reasoning paradigm that combines Answer Set Programming (ASP) with Constraint Processing and Satisf

researcharxiv-cs-ai

FastCentNN: Accelerating Centroid Neural Network with Entropy Proxy

arXiv:2607.13613v1 Announce Type: cross Abstract: Centroid neural network (CentNN) is an unsupervised competitive learning algorithm in which centroid splitting is triggered only after strict local st

Local Ai

Federated Explainable Artificial Intelligence: Roles, Architectures, Evaluation, and Open Challenges

arXiv:2607.13045v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a key paradigm for privacy-preserving collaborative model training across distributed and heterogeneous data so

local-aiarxiv-cs-ai

Fine-Grained Vision-Language Pretraining with Organ-Conditioned Pattern Tokens for CT Understanding

arXiv:2607.13892v1 Announce Type: new Abstract: Computed tomography (CT) vision-language pretraining from paired volumes and radiology reports is a scalable yet challenging task. Existing methods comm

Fire as a Service: Augmenting Robot Simulators with Thermally and Visually Accurate Fire Dynamics

arXiv:2603.19063v2 Announce Type: replace Abstract: Most existing robot simulators prioritize rigid-body dynamics and photorealistic rendering, but largely neglect the thermally and optically complex

FM^2: Unified Federated Foundation Models for Heterogeneous Multimodal Medical Imaging

arXiv:2607.13386v1 Announce Type: new Abstract: Building foundation models for medical imaging requires pooling data across institutions, yet privacy regulations prohibit centralized aggregation. Exis

From Surface Forecasting to Observability Forecasting: A Latent World Model for Cloud-Aware EO Monitoring

arXiv:2607.13651v1 Announce Type: new Abstract: The bottleneck of Earth Observation processing chains is not the arrival of new imagery but whether the surface is actually visible when the image arriv

Generalizable VLA Finetuning via Representation Anchoring and Language-Action Alignment

arXiv:2607.13429v1 Announce Type: cross Abstract: Finetuning a pretrained vision-language model (VLM) on robot demonstrations via behavior cloning (BC) has become the standard recipe for vision-langua

GFlowRL: Scaling Distribution-Matching RL to Large Language Models

arXiv:2607.13394v1 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) offer a promising alternative to reward-maximizing reinforcement learning (RL) for large reasoning models, encour

researcharxiv-cs-lg

GNN-DIP: Neural Corridor Selection for Decomposition-Based Motion Planning

arXiv:2603.12361v2 Announce Type: replace Abstract: Motion planning through narrow passages remains a core challenge: sampling-based planners rarely place samples inside these narrow but critical regi

safetyarxiv-cs-ro

GPOcc++: Unified Sparse Gaussian Occupancy Prediction with Visual Geometry Priors

arXiv:2607.13481v1 Announce Type: new Abstract: Accurate 3D scene understanding is fundamental to embodied intelligence and autonomous driving, where 3D occupancy provides a unified representation of

GPUSimBench: Towards Scalable and Reliable GPU-Accelerated Simulators in Embodied AI

arXiv:2607.13059v1 Announce Type: new Abstract: Data-driven embodied AI is rapidly transitioning into a paradigm that scales training through massively parallel simulation, where GPU-accelerated simul

HEDGEHOG: Hierarchical Evaluation of Drug Generators Through Rigorous Filtration

arXiv:2607.13155v1 Announce Type: new Abstract: Generative molecular models can support early drug discovery by proposing new candidate compounds de novo. In practice, useful candidates must balance t

Human4K: A Large-Scale 4K Multi-View Mocap Dataset for Whole-Body 3D Human Reconstruction

arXiv:2607.13646v1 Announce Type: cross Abstract: Recent advances in 3D human reconstruction have improved overall performance, yet current models still fail in the most challenging real-world scenari

Inverse-LLaVA: Rethinking Multimodal Alignment via Text-to-Vision Mapping

arXiv:2508.12466v2 Announce Type: replace-cross Abstract: Traditional multimodal learning approaches rely on alignment pre-training to bridge vision and language modalities, typically by projecting vi

Joint On-and-Off Policy Learning for Vision-and-Language Navigation

arXiv:2607.13461v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) necessitates an embodied agent to navigate in the physical world by adhering to natural language instructions. Rece

safetyarxiv-cs-ro

Learning Robust Execution in Robotic Manipulation with Agentic Reinforcement Learning

arXiv:2607.13818v1 Announce Type: new Abstract: Robotic manipulation poses fundamental challenges due to uncertainty, long-horizon execution, and compounding errors, which can easily destabilize execu

Left-right asymmetry in predicting brain activity from LLMs' representations emerges with their formal linguistic competence

arXiv:2602.12811v2 Announce Type: replace-cross Abstract: When humans and large language models (LLMs) process the same text, activations in the LLMs correlate with brain activity measured, e.g., with

researcharxiv-cs-ai

Lighthouse RL: Sample-Efficient Circuit Optimization via Strategic Reset Points

arXiv:2607.14008v1 Announce Type: new Abstract: In this paper, we introduce Lighthouse RL, a sample-efficient reinforcement learning (RL) approach for analog circuit sizing. Traditional methods lack g

MASPRM: Multi-Agent System Process Reward Model

arXiv:2510.24803v3 Announce Type: replace-cross Abstract: Inference-time search over multi-agent systems (MAS) wastes compute when it cannot identify which agent's intermediate message advanced progre

Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents

arXiv:2607.13591v1 Announce Type: cross Abstract: Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks. Yet nearly all existing approach

Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs

arXiv:2601.02023v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) increasingly utilize massive context windows as working memory for autonomous tasks, their reliability fluctua

Operational Evidence Gaps for LLMs in Fraud Detection and Trust-and-Safety Workflows

arXiv:2607.13078v1 Announce Type: cross Abstract: LLMs are now proposed for fraud detection, scam investigation, content moderation, and other trust-and-safety workflows. Much of the public literature

PiVoT: A Variational Solution for Real-time Large-scale Multi-object Detection and Tracking under Heavy Clutter

arXiv:2607.13891v1 Announce Type: cross Abstract: Multi-object detection and tracking from noisy point clouds remain challenging in many data-scarce radar applications. Current Bayesian trackers based

Quantum Circuit Vision: Cost-Aware Evaluation of Visual AI Agents for Quantum Code Generation

arXiv:2607.10057v1 Announce Type: cross Abstract: Can AI agents visually comprehend quantum circuit diagrams and generate verified executable code--and at what cost? We present Quantum Circuit Vision,

Reassessing Muon for Matrix Factorization

arXiv:2607.13246v1 Announce Type: cross Abstract: Muon has recently emerged as a strong optimizer for large-scale deep learning, where it reshapes gradient updates through approximate orthogonalizatio

researcharxiv-cs-ai

Reverse to Advance: Teleoperation-Cost Effective Hard Policy Learning from Reversed Easy Tasks

arXiv:2607.13455v1 Announce Type: new Abstract: High-quality teleoperation datasets are costly to collect, particularly for hard tasks. We observe that many tasks exhibit directional asymmetry: comple

safetyarxiv-cs-ro

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation

arXiv:2607.13897v1 Announce Type: new Abstract: The broadcast nature of wireless channels exposes radio-frequency (RF) networks to anomalous and malicious transmissions, making anomaly detection a fun

S-squared-VLA: Decoupling Semantic and Spatial Streams in Vision-Language-Action Models for Autonomous Driving

arXiv:2607.13926v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable potential for high-level reasoning in autonomous driving, yet they fundamentally struggle to

SARFA: Segment Anything with Radiomic Feature Alignment

arXiv:2607.13323v1 Announce Type: new Abstract: The Segment Anything Model (SAM) has demonstrated strong generalizability across a variety of segmentation tasks. However, SAM often struggles in situat

ScanFocus: A Coarse-to-Fine Framework for Spatio-Temporal Video Grounding

arXiv:2607.13421v1 Announce Type: cross Abstract: Spatio-Temporal Video Grounding (STVG) aims to retrieve the visual trajectory of a specific object from a video stream as described by a natural langu

Screening Is Effective for Visual Recognition

arXiv:2607.13983v1 Announce Type: new Abstract: Vision Transformer (ViT) has been widely used as a powerful framework for modeling global dependencies among image patches. However, its core component,

researcharxiv-cs-cv

Self-Improving is Often Sudden: Enlightenment-style Finetuning for Large-Scale Models

arXiv:2607.13395v1 Announce Type: new Abstract: The pursuit of autonomously self-improving models has attracted growing interest in the era of large-scale foundation models. Drawing inspiration from t

researcharxiv-cs-lg

Self-Supervised Visual Representation Learning: Pretrain-Finetuning or Joint Training?

arXiv:2607.13192v1 Announce Type: new Abstract: Self-supervision is a powerful technique for learning visual representations from unlabeled data. Existing techniques primarily adopt a two-stage approa

Applications

Semantic Anchoring for Robotic Action Representations

arXiv:2607.13597v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models inherit rich semantic representations from pretrained Vision-Language Models, yet fine-tuning on limited robot dem

applicationsarxiv-cs-ai

Set-shifting Behavioral Test for Harnessed Agents

arXiv:2607.13396v1 Announce Type: new Abstract: What happens to an LLM agent's tool choice when the reliable tool silently changes within an ongoing session? We borrow set-shifting from cognitive psyc

ShortOPD: Recovering Pruned LLMs with Short-to-Long On-Policy Distillation

arXiv:2607.13124v1 Announce Type: cross Abstract: Structured pruning is a hardware-friendly way to compress LLMs, but it is mostly validated on multiple-choice recognition tasks, while the same compre

SIVA-RL: Sensitivity-Invariance Visual Alignment for Multimodal Reinforcement Learning

arXiv:2607.13931v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) drives multimodal reasoning, but answer-level correctness does not guarantee that a vision-languag

SteinGate: Tail-Sensitive Safe Reinforcement Learning via Stein Discrepancy

arXiv:2607.13175v1 Announce Type: cross Abstract: Safe reinforcement learning typically enforces safety by bounding expected cumulative costs, a criterion that often fails to detect rare but catastrop

Applications

STKAN: Kolmogorov-Arnold Networks for Spatio-Temporal Forecasting

arXiv:2607.13108v1 Announce Type: cross Abstract: Real-world traffic data exhibit heterogeneous spatial correlations and nonlinear temporal dynamics, posing substantial challenges for accurate spatio-

applicationsarxiv-cs-ai

The Dynamic Verifiable Multi-Agent Human Agentic Loyalty Loop (DVM-HALL) Model and the Net Human-Agent Score (NHAS) in Autonomous Commerce

arXiv:2607.13998v1 Announce Type: cross Abstract: The rapid proliferation of Agentic Artificial Intelligence fundamentally disrupts traditional customer loyalty paradigms. As AI evolves from passive r

The Perplexity Trap: When Patent Law Makes Human Writing Look Like AI

arXiv:2607.13044v1 Announce Type: cross Abstract: The European Patent Office (EPO) reported record filings in 2025, and the 2026 EPO Guidelines hold applicants strictly responsible for LLM-assisted co

Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Models

arXiv:2607.13860v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in 2D medical image understanding, their extension to 3D volumetric

researcharxiv-cs-cv

Traffic-Aware Randomized Smoothing for LLM-Based Network Intrusion Detection

arXiv:2607.13801v1 Announce Type: cross Abstract: Large language model (LLM)-based intrusion detection systems (IDS) are increasingly studied for security monitoring, yet their robustness against feas

UniPhysGen: Unified Physical Grounding for Simulation-Ready 3D Assets

arXiv:2607.13586v1 Announce Type: new Abstract: Physically grounded 3D assets are increasingly important for embodied AI and robotic simulation. However, most existing 3D assets lack unified physical