Search: “models”

CSympNet-ID: conformal-symplectic map learning for linearly damped Hamiltonian systems

arXiv:2607.03339v1 Announce Type: new Abstract: Learning dissipative dynamics from discrete observations is essential for reliable long-horizon prediction and physically meaningful parameter identific

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CuBAS: Information Geometric Curvature-Based Adaptive Sampling for Supervised Classification

DGX agent

arXiv:2607.03145v1 Announce Type: cross Abstract: The informativeness of a training set is as consequential as its size, yet most sampling strategies remain agnostic to the intrinsic geometry of the d

model-releasesarxiv-cs-ai

7 Jul 2026

Decomposition for Bayesian Networks: Local and Parallel Inference

arXiv:2607.04650v1 Announce Type: cross Abstract: Probabilistic inference in high-dimensional Bayesian networks is difficult because exact manipulation of the joint distribution scales exponentially w

Local Ai

DELTAVID: Enhancing Fine-Grained Spatiotemporal Perception with Cross-Video Differences

arXiv:2607.02551v1 Announce Type: cross Abstract: Video multimodal large language models have made strong progress on open-ended video understanding, but they still lack precise local spatiotemporal p

local-aiarxiv-cs-ai

Detecting Answer-Driven Reasoning in LLM-Based Educational Tutors via Truncated Chain-of-Thought Auditing

arXiv:2607.04572v1 Announce Type: new Abstract: Large language model (LLM) tutors often produce fluent step-by-step explanations, but a correct and pedagogically formatted response does not guarantee

tutorialsarxiv-cs-ai

Agents

Do GUI Agents Believe Their Eyes? Diagnosing State-Belief Reliance on Pixels versus Structure

arXiv:2607.04334v1 Announce Type: new Abstract: Multimodal GUI agents read an interface through two redundant channels: the rendered pixels of a screenshot and a serialized structure such as a DOM or

agentsarxiv-cs-ai

Applications

DS-SAC: Density Search for Sample Consensus

arXiv:2607.03972v1 Announce Type: new Abstract: Robust geometric model estimation is a fundamental problem in computer vision. RANSAC and its variants remain widely used for this task; however, they r

applicationsarxiv-cs-cv

EM3M: An Electron Micrograph Dataset for Microstructural Segmentation and Generation

arXiv:2508.16239v2 Announce Type: replace Abstract: Quantitative microstructural characterization is fundamental to materials science, and electron micrographs (EMs) provide indispensable high-resolut

Estimating Individual Tree Height and Species from UAV Imagery

arXiv:2603.23669v2 Announce Type: replace-cross Abstract: Accurate estimation of forest biomass, a major carbon sink, relies heavily on tree-level traits such as height and species. Unoccupied Aerial

Evaluating Agentic Harness Systems for Autonomous Computational Pathology

arXiv:2607.02598v1 Announce Type: new Abstract: Autonomous computational pathology (ACP) converts high-level pathology analysis goals into executable, traceable and clinically bounded workflows. Reali

EVAS: Efficient Multimodal Temporal Forgery Localization via Audio-Visual Synergy and Steered Boundary Calibration

arXiv:2607.04472v1 Announce Type: new Abstract: The rapid proliferation of artificial intelligence-generated content necessitates reliable multimodal forensics. Beyond video-level binary classificatio

EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer

arXiv:2607.05202v1 Announce Type: new Abstract: Agent self-evolution in long-horizon LLM systems is largely procedural: useful experience is not merely stored information, but reusable procedures for

Evolutionary Guided Decoding: Iterative Value Refinement for LLMs

arXiv:2503.02368v4 Announce Type: replace-cross Abstract: While guided decoding, especially value-guided methods, has emerged as a cost-effective alternative for controlling language model outputs wit

safetyarxiv-cs-ai

Explainable AI for Screening Abuse-Related Trauma in Bangladeshi Children: A Training-Free Multimodal Framework Evaluated on Noise-Aware Synthetic Data

arXiv:2607.04010v1 Announce Type: new Abstract: Bangladesh has an estimated 1.17 mental-health professionals per 100,000 population and only six child psychiatrists nationwide. No Bengali-language, cu

Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks

arXiv:2503.10496v2 Announce Type: replace-cross Abstract: Modeling natural phenomena with artificial neural networks (ANNs) often provides highly accurate predictions. However, ANNs often suffer from

tutorialsarxiv-cs-ai

ExpoMotion: A Large-Scale Benchmark and A Householder Projection Network for Multi-Exposure Fusion

arXiv:2607.03110v1 Announce Type: new Abstract: Multi-Exposure Fusion (MEF) effectively extends dynamic range, but practical deployment is hindered by motion-induced ghosting and the scarcity of high-

F-ACVAE: A Federated Adaptive Conditional Variational Auto-Encoder for Privacy-Preserving Intrusion Detection in IoT Networks

arXiv:2607.04698v1 Announce Type: new Abstract: The rapid proliferation of Internet of things (IoT) devices has significantly expanded the cyber-attack surface, necessitating robust and privacy-preser

Faithfulness to Refusal: A Causal Audit of Neuron Selectors

arXiv:2607.05355v1 Announce Type: new Abstract: Attribution scores increasingly identify which neuron rows of a language model matter for applications such as pruning, interpretability, and editing fo

safetyarxiv-cs-cl

FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity

arXiv:2607.03763v1 Announce Type: cross Abstract: Federated Transformer training increasingly relies on local AdamW, whose adaptive updates can provide much stronger local progress than SGD-based trai

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging

arXiv:2607.04158v1 Announce Type: cross Abstract: Federated learning (FL) is severely hindered by statistical heterogeneity due to variations in scanners, acquisition protocols, and patient population

FormalRx: Rectify and eXamine Semantic Failures in Autoformalization

model-releasesarxiv-cs-cl

arXiv:2607.04655v1 Announce Type: new Abstract: The veracious semantic alignment in autoformalization is significant for formal mathematical reasoning. However, existing evaluations provide only opaqu

Framework and Multi-modal Dataset for Roadwork Zone Detection and Geo-localization

arXiv:2607.04330v1 Announce Type: new Abstract: Autonomous vehicles often rely on high-definition (HD) maps for navigation; however, these maps are not frequently updated and often lack semi-static in

Generative Semantic Multi-Object Tracking: A Large-Scale Benchmark and an MLLM-Driven Reasoning Framework

arXiv:2601.06550v3 Announce Type: replace-cross Abstract: Semantic Multi-Object Tracking (SMOT) is evolving from purely geometric localization toward comprehensive video understanding. However, existi

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation

arXiv:2607.03869v1 Announce Type: cross Abstract: Referring remote sensing image segmentation isolates the object named by a natural-language expression in an aerial image. Existing training-free meth

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection

arXiv:2607.03862v1 Announce Type: new Abstract: AI-generated images have proliferated rapidly, motivating extensive research. Most existing AI-generated image detectors are developed and evaluated und

GLM-5 Serving Parameter Tuning for OpenClaw: Single-Deployment MaaS Inference Optimization for Long-Context Agent Workloads

arXiv:2607.02518v1 Announce Type: cross Abstract: OpenClaw requests are dominated by long, tool-augmented prefixes, including system prompts, conversation history, and tool outputs fed back into the c

GMODiff: One-Step Gain Map Refinement with Diffusion Priors for HDR Reconstruction

arXiv:2512.16357v3 Announce Type: replace Abstract: Pre-trained Latent Diffusion Models (LDMs) have recently shown strong perceptual priors for low-level vision tasks, making them a promising directio

tutorialsarxiv-cs-cv

Google Cloud Labs: Accelerate AI with Cloud Run

model-releasesgoogle-cloud-ai

Moving Beyond the Prototype The AI landscape has shifted. While 'vibe coding' with tools like Antigravity and AI Studio lets you build and deploy complex agents in minutes, the real work begins on 'Da

Governing Generative AI Across Financial Institutions: An SR 26-2-Compatible Framework for Generative AI Risk Control

arXiv:2607.04103v1 Announce Type: cross Abstract: The release of SR 26-2 marks a significant modernization of U.S. model risk management by replacing SR 11-7 with a more risk-based and materiality-sen

safetyarxiv-cs-lg

HCSU: A Dataset and Benchmark for Fine-Grained Historical Calligraphy Style Understanding

arXiv:2607.04147v1 Announce Type: cross Abstract: Automated fine-grained perception of calligraphy styles--a task vital to cultural heritage preservation--remains a critical challenge for Large Vision

Hierarchical Multi-to-Single-Modal Knowledge Distillation for Disruption Prediction in EAST

arXiv:2607.04241v1 Announce Type: cross Abstract: Plasma disruption is a critical threat to tokamak safety. Existing data-driven predictors mainly rely on time-series diagnostic signals, while visible

HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control

arXiv:2607.03449v1 Announce Type: cross Abstract: Current Vision-Language-Action (VLA) models excel at robotic manipulation but often struggle with non-Markovian tasks requiring long-term memory and r

Hyperparameter Transfer in Graph Neural Networks

arXiv:2607.05017v1 Announce Type: cross Abstract: The performance of deep learning models crucially depends on the settings of hyperparameters like learning rate, initialization scale, and weight deca

ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing

arXiv:2607.04675v1 Announce Type: new Abstract: This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Gra

If you care about AI, and want a nuanced view, you should watch this. I promise it will be worth your time.

model-releasesgary-marcus--x

If you care about AI, and want a nuanced view, you should watch this. I promise it will be worth your time. An excellent video from the @WorldSciFest featuring @GaryMarcus , in which he discusses—amon

iFLYTEK-Embodied-Omni Technical Report

arXiv:2607.02542v1 Announce Type: new Abstract: General-purpose embodied agents must understand multimodal instructions, anticipate how their environment will evolve, and produce precise control actio

InFlux++: Real and Synthetic Data for Estimating Dynamic Camera Intrinsics

arXiv:2607.05389v1 Announce Type: new Abstract: Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms assume fixed intrinsics throughout a video, an assump

Local Ai

Inpainting U-Net for seamless pedestrian-level wind prediction across urban morphologies

arXiv:2607.02560v1 Announce Type: new Abstract: Pedestrian-level wind prediction is essential for urban design and wind-comfort assessment, but high-fidelity simulations such as LES remain computation

local-aiarxiv-cs-cv

InternVLA-A1.5: Unifying Understanding, Latent Foresight, and Action for Compositional Generalization

arXiv:2607.04988v1 Announce Type: new Abstract: Unified models for robot manipulation aim to equip one policy with both the semantic priors of pretrained VLMs and the physical dynamics learned through

safetyarxiv-cs-ro

Interpretable Human-Label-Free Deep Learning for Real-Bogus Classification with Uncertainty Quantification

arXiv:2607.05393v1 Announce Type: cross Abstract: Time-domain surveys generate many transient candidates, making Real-Bogus classification a critical step in automated discovery pipelines. Reliable la

InverseCrafter: Efficient Video ReCapture as a Latent Domain Inverse Problem

arXiv:2512.05672v2 Announce Type: replace-cross Abstract: Recent approaches in controllable novel view video generation often rely on fine-tuning pre-trained Video Diffusion Models (VDMs). This domina

IPDiff: Diffusion-driven ORSI Salient Object Detection with Information Reconstruction and Multi-Prior Guidance

arXiv:2607.03696v1 Announce Type: new Abstract: Existing Salient Object Detection in Optical Remote Sensing Image (ORSI-SOD) methods mainly adopt the static inference strategy, which uses fixed traine

Knowing When to Stop: Predicting Execution-Consistency Convergence in Text-to-SQL

model-releasesarxiv-cs-cl

arXiv:2607.03991v1 Announce Type: cross Abstract: Repeated LLM calls are the standard way to estimate how trustworthy a Text-to-SQL result is: run the pipeline multiple times, judge each SQL execution

Language-guided Medical Image Segmentation with Target-informed Multi-level Contrastive Alignments

arXiv:2412.13533v4 Announce Type: replace Abstract: Medical image segmentation is a fundamental task in numerous medical engineering applications. Recently, language-guided segmentation has shown prom

Learning to Visually Connect Actions and their Effects

arXiv:2401.10805v4 Announce Type: replace-cross Abstract: We introduce the novel concept of visually Connecting Actions and Their Effects (CATE) in video understanding. CATE can have applications in a

tutorialsarxiv-cs-ai

Leveraging Pathology Co-occurrence for Test-Time Adaptation in Chest X-Ray Diagnosis

arXiv:2607.03715v1 Announce Type: new Abstract: Medical imaging models often degrade when deployed at new clinical sites due to differences in imaging equipment, protocols, and patient populations. Te

researcharxiv-cs-cv

LiNO: Lifting based multiresolution neural operator

arXiv:2607.02715v1 Announce Type: new Abstract: Recently, neural operators have shown promising outcomes for learning solution operators of differential equations directly from data. This framework le

LLM-Driven CI-CD Workflow Intelligence for Cyber Systems Engineering

arXiv:2607.04579v1 Announce Type: cross Abstract: CI/CD workflows have become executable operational policy: they decide what gets built, tested, released, and deployed, and they mediate how maintaine