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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

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Safety

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

DGX agent

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

7 Jul 2026

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

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

Tutorials

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

MARLIN: De Novo Molecular Structure Elucidation from Tandem Mass Spectra without a Ground-Truth Formula

arXiv:2607.04774v1 Announce Type: new Abstract: Untargeted tandem mass spectrometry (MS/MS) detects thousands of small molecules per biological sample, yet most go unidentified because they are absent

Medical Heuristic Learning: An LLM-Driven Framework for Interpretable and Auditable Clinical Decision Rules

arXiv:2606.16337v3 Announce Type: replace Abstract: Predictive modeling for clinical decision support requires not only strong predictive performance but also transparent decision logic. Although deep

MemPose: Category-level Object Pose Estimation with Memory

arXiv:2607.04930v1 Announce Type: cross Abstract: In the pursuit of robust and generalizable category-level object pose estimation, most existing methods adopt parametric formulations that learn effec

Octax: Accelerated CHIP-8 Arcade Environments for Reinforcement Learning in JAX

arXiv:2510.01764v3 Announce Type: replace Abstract: Reinforcement learning (RL) research requires diverse, challenging environments that are both tractable and scalable. While modern video games may o

OpenTinker: Separating Concerns in Agentic Reinforcement Learning

arXiv:2601.07376v2 Announce Type: replace Abstract: We introduce extsc{OpenTinker}, an open infrastructure for training large language model (LLM) agents with many LoRA-backed policies over shared exe

pFedNavi: Structure-Aware Personalized Federated Vision-Language Navigation for Embodied AI

arXiv:2602.14401v2 Announce Type: replace-cross Abstract: Vision-Language Navigation VLN requires large-scale trajectory instruction data from private indoor environments, raising significant privacy

Phi-SegNet: Phase-Integrated Supervision for Medical Image Segmentation

arXiv:2601.16064v2 Announce Type: replace-cross Abstract: Deep learning has substantially advanced medical image segmentation, yet achieving robust generalization across diverse imaging modalities and

Predicting Drafted Deck Strength for 'Magic: the Gathering'

arXiv:2607.04782v1 Announce Type: cross Abstract: Many real-world games do not admit a fixed, compact rule set: instead, their dynamics are defined by interactions among a large and often evolving col

ProxyUp: Training-Free Proxy-Conditioned Video Generation for Controllable Dynamics

arXiv:2607.03732v1 Announce Type: new Abstract: Precise control over complex dynamics remains challenging for modern video generative models, as text prompts alone often cannot specify physically plau

safetyarxiv-cs-cv

Rational Inverse Reasoning: Few-Shot Imitation by Inferring Intent through Planning

arXiv:2508.08983v2 Announce Type: replace-cross Abstract: Humans can learn a new manipulation task from one or two demonstrations and then perform it in a new room, with new objects, under new constra

Applications

Relevance-Based Embeddings: Lightweight Candidate Retrieval via Heavy-Ranker Calls

arXiv:2607.03515v1 Announce Type: cross Abstract: In many machine learning applications, the most relevant items for a query should be efficiently retrieved. The relevance function is usually an expen

applicationsarxiv-cs-lg

Rethinking AI-Generated Text Detection: A Strong Baseline and the Distribution-Shift Problem That Remains

model-releasesarxiv-cs-cl

arXiv:2607.03680v1 Announce Type: cross Abstract: Recent AI-generated text detection work often introduces a new benchmark together with a specialized detector tailored to it. We revisit this practice

Reward Lightning: Fast Video Generation via Homologous Preference Distillation

arXiv:2607.03960v1 Announce Type: new Abstract: Achieving simultaneous preference alignment and distillation acceleration in video diffusion models remains an open challenge. Existing methods optimize

safetyarxiv-cs-cv

Robust Sparse Bayesian Learning Based on Minimum Error Entropy for Noisy High-Dimensional Brain Activity Decoding

arXiv:2508.11657v2 Announce Type: replace-cross Abstract: Objective: Sparse Bayesian learning provides an effective framework to solve high-dimensional problems in brain signal decoding. However, conv

Hardware

RoMa v2: Harder Better Faster Denser Feature Matching

arXiv:2511.15706v3 Announce Type: replace Abstract: Dense feature matching aims to estimate all correspondences between two images of a 3D scene and has recently been established as the gold standard

hardwarearxiv-cs-cv

Safe Inference-Time Alignment via Lagrangian Reward Augmentation

arXiv:2607.02781v1 Announce Type: cross Abstract: Inference-time alignment steers a frozen language model during decoding using auxiliary reward signals, avoiding the cost of repeated weight updates.

SalAngaBhava: A Sinhala Market Dataset for Aspect-based Sentiment Analysis

model-releasesarxiv-cs-cl

arXiv:2607.05259v1 Announce Type: new Abstract: Sentiment analysis has been a primary domain under Natural Language Processing (NLP) from its inception as it plays a vital role in both real-world and

Score-Regularized Joint Sampling with Importance Weights for Flow Matching

arXiv:2511.17812v3 Announce Type: replace-cross Abstract: Flow matching models effectively represent complex distributions, yet estimating expectations of functions of their outputs remains challengin

SiamixFormer: a fully-transformer Siamese network with temporal Fusion for accurate building detection and change detection in bi-temporal remote sensing images

arXiv:2208.00657v2 Announce Type: cross Abstract: Building detection and change detection using remote sensing images can help urban and rescue planning. Moreover, they can be used for building damage

Silicon Sampling via Cross-Survey Transfer

arXiv:2607.03091v1 Announce Type: new Abstract: Silicon sampling-using large language models (LLMs) to simulate human survey respondents-has emerged as a promising approach for augmenting traditional

SilvaScenes: Tree Detection and Species Classification from Under-Canopy Images in Natural Forests

arXiv:2510.09458v2 Announce Type: replace-cross Abstract: Interest in forestry automation is growing alongside rapid advances in deep learning. In particular, tree detection and taxonomic classificati

Simple-to-Complex Structured Demonstrations for Vision-Language-Action Learning

arXiv:2607.04591v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated strong capabilities in robotic manipulation by integrating visual perception, language understan

SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe

arXiv:2607.03451v1 Announce Type: cross Abstract: While skill optimization for autonomous agents has gained traction, existing methods rely on complex pipelines. This leaves a fundamental question una

SLAM: Structured and Localized Analytic Manifold Adaptation for Lifelong VPR

arXiv:2607.04764v1 Announce Type: cross Abstract: Visual Place Recognition (VPR) in lifelong deployment requires continuous adaptation to new environments without catastrophic forgetting. In this pape

SMF-VO: Direct Ego-Motion Estimation via Sparse Motion Fields

arXiv:2511.09072v2 Announce Type: replace-cross Abstract: Traditional Visual Odometry (VO) and Visual Inertial Odometry (VIO) methods rely on a 'pose-centric' paradigm, which computes absolute camera

SovereignNegotiation-Bench: Evaluating User-Owned Personal Agents In Delegated Bargaining Under Privacy, Consent, Evidence, And Institutional Pressure

arXiv:2607.02814v1 Announce Type: cross Abstract: Personal agents will increasingly negotiate on behalf of users: splitting costs with other personal agents, appealing platform decisions, escalating s

Applications

SpreadsheetArena: Decomposing Preference in LLM Generation of Spreadsheet Workbooks

arXiv:2603.10002v2 Announce Type: replace-cross Abstract: We consider the task of end-to-end spreadsheet generation, where language models produce spreadsheet artifacts to satisfy users' explicit and

applicationsarxiv-cs-ai

Statistically Meaningful Geometry (SMG) Beyond the Euclidean Paradigm, with Application to Generative AI

arXiv:2607.03329v1 Announce Type: new Abstract: Conventional uniform convergence bounds and empirical risk minimization break down in massive over-parameterized models, such as large language transfor

researcharxiv-cs-lg