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Conformal Prediction with Macro-Coverage Guarantees

arXiv:2606.28598v1 Announce Type: cross Abstract: Prediction sets should have high coverage to be useful, but some coverage notions are more practically relevant than others. In the classification set

Connectivity Estimation using Stochastic Graph Heat Modelling

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DGX agent

arXiv:2606.29098v1 Announce Type: cross Abstract: A growing number of techniques leverage the spatial structures that underlie many real-world datasets. Despite these advances, the complementary task

applicationsarxiv-cs-lg

30 Jun 2026

Consensus Clustering of Free-Viewing Gaze Data: New Insights into Human-Information Interaction

arXiv:2606.30035v1 Announce Type: new Abstract: Free-viewing gaze data provides a rich, task-free window into human visual attention. Conventional exploratory data analysis of the data provides user a

researcharxiv-cs-cv

Consistency as Inductive Bias: Learning Cross-View Invariance for Robust Multimodal Reasoning

arXiv:2606.29812v1 Announce Type: new Abstract: Inductive biases steer learning toward generalizable solutions by encoding task structure. In this work, we identify a crucial missing bias in MLLMs: cr

safetyarxiv-cs-cv

Constrained Tabular Diffusion for Finance

arXiv:2606.28674v1 Announce Type: cross Abstract: Generative models in finance face the dual challenge of producing realistic data while satisfying strict regulatory and economic objectives, a require

applicationsarxiv-cs-ai

Contact-Anchored Proprioceptive Odometry for Legged and Wheel-Legged Robots

arXiv:2602.17393v3 Announce Type: replace Abstract: Reliable odometry for legged robots without cameras or LiDAR remains challenging due to IMU drift and noisy joint velocity sensing. This paper prese

researcharxiv-cs-ro

Tutorials

Contrastive vision-language learning with paraphrasing and negation

arXiv:2511.16527v2 Announce Type: replace Abstract: Contrastive vision-language models continue to be the dominant approach for image-text retrieval. Contrastive Language-Image Pre-training (CLIP) tra

tutorialsarxiv-cs-cv

Convergence of Continual Learning in Homogeneous Deep Networks

arXiv:2606.30559v1 Announce Type: new Abstract: We characterize weakly regularized continual classification in homogeneous models as sequential projections onto task margin sets. This result generaliz

Conversational Domain Adaptation of IndicTrans2 across 21 Indic Languages via Experience Replay and Model Soups

arXiv:2606.29024v1 Announce Type: new Abstract: IndicTrans2 is the strongest open English to Indic translation system, but like most systems it is trained on general text and tends to sound stiff on c

researcharxiv-cs-cl

Conversational Query Engine for Mixed-Modality Heterogeneous Enterprise Data Sources

arXiv:2606.28370v1 Announce Type: cross Abstract: Enterprise business intelligence queries span structured warehouses and unstructured document repositories -- modalities with fundamentally different

CORE: Common Outcome Regularities from Action-Free Visual Demonstrations for Robot Manipulation

arXiv:2606.29517v1 Announce Type: new Abstract: Robot imitation learning often relies on costly robot demonstrations, while abundant action-free visual demonstrations, such as human videos, are diffic

safetyarxiv-cs-ro

Agents

CORE Planner: Contextual-memory Oriented Reinforcement-learning in Unknown Environments for Robot Navigation

arXiv:2606.29222v1 Announce Type: new Abstract: Autonomous navigation in unknown environments requires a robot to efficiently reach a predefined goal while exploring without prior maps. Although progr

agentsarxiv-cs-ro

Correct codes for the wrong reasons? validating LLMs as measurement instruments for theoretical constructs

arXiv:2606.28574v1 Announce Type: cross Abstract: When a large language model (LLM) codes a construct in text as a human annotator would, that agreement makes the LLM a reliable coder. Yet reliability

CORTEX: High-Quality Cross-Domain Organization of Web-Scale Corpora through Ontological Corpus Graph

model-releasesarxiv-cs-cl

arXiv:2606.30175v1 Announce Type: new Abstract: The continuous evolution of large language models drives escalating demands on data scale and quality, and as different training stages impose increasin

CoSPlan: Corrective Sequential Planning via Scene Graph Incremental Updates

model-releasesarxiv-cs-cv

arXiv:2512.10342v3 Announce Type: replace Abstract: Vision Language Models (VLMs) have shown promising planning capabilities, yet their success remains confined to the text domain, leaving visual deci

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

arXiv:2511.02734v3 Announce Type: replace Abstract: Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability

CouCE: A Unified Causal Framework for Debiased Deep Metric Learning

arXiv:2606.30365v1 Announce Type: new Abstract: Deep Metric Learning (DML) often struggles with zero-shot generalization because standard objectives inherently capture what co-occurs rather than what

researcharxiv-cs-cv

Counterfactual Residual Data Augmentation for Regression

arXiv:2606.28460v1 Announce Type: cross Abstract: Data-driven modeling in real-world regression tasks often suffers from limited training samples, high collection costs, and noisy observations. Inspir

Coverage-Driven KV Cache Eviction for Efficient and Improved Inference of LLM

arXiv:2606.29563v1 Announce Type: cross Abstract: Large language models (LLMs) excel at complex tasks like question answering and summarization, thanks to their ability to handle long-context inputs.

Covering the Unseen: Information Demand Coverage Optimization for Retrieval-Augmented Generation

arXiv:2606.29328v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) typically treats context selection as ranking chunks against a single query embedding. This assumption breaks dow

CRAFT: Counterfactual Credit Assignment from Free Sibling Rollouts for Self-Distilled Agentic Reinforcement Learning

arXiv:2606.29476v1 Announce Type: cross Abstract: Self-distilled agentic reinforcement learning augments trajectory-level reward with a token-level distillation loss, using as its teacher the same pol

safetyarxiv-cs-ai

Critical Interval MSE: Toward Reliable Offline Validation for Robot Manipulation Policies

arXiv:2606.29898v1 Announce Type: cross Abstract: Real-world evaluation is the gold standard for robot policies because it tests them against the physical conditions and deployment challenges they are

safetyarxiv-cs-ai

Cross-Modal Iteration Distillation for Robust IHD Screening: The IDNet Framework and A New Benchmark

model-releasesarxiv-cs-cv

arXiv:2606.30027v1 Announce Type: new Abstract: Color Fundus Photography (CFP) offers a low-cost and non-invasive route for ischemic heart disease (IHD) screening, but current studies are limited by s

Cross-Resolution Semantic Transfer for Robust Text-to-Image Retrieval in Low-Resolution Surveillance

arXiv:2606.30458v1 Announce Type: new Abstract: Text-to-image person re-identification (TIPR) retrieves target persons using natural language descriptions. However, existing methods largely overlook r

applicationsarxiv-cs-cv

Cross-Session 3D LiDAR and Camera Fusion for Robust Localization of Unmanned Aerial Vehicles in GPS-Denied Environments

arXiv:2606.28951v1 Announce Type: new Abstract: Accurate localization of unmanned aerial vehicles (UAVs) is essential for applications such as structural health monitoring, especially in environments

researcharxiv-cs-ro

Cross-Spectral Stereo Inertial Odometry

arXiv:2606.29757v1 Announce Type: new Abstract: Standard stereo VIO focuses exclusively on the benefit of metric scale via single-spectrum baselines, often overlooking the risks of spectral redundancy

researcharxiv-cs-ro

Cross-Temporal Sinhala OCR: Page-Level Adaptation and Diachronic Analysis

model-releasesarxiv-cs-cl

arXiv:2606.29378v1 Announce Type: new Abstract: Sinhala is a morphologically rich abugida spoken by roughly 16 million people in Sri Lanka, and to date, there are no publicly available real-world data

CrossWeaver: Cross-modal Weaving for Arbitrary-Modality Semantic Segmentation

arXiv:2604.02948v2 Announce Type: replace Abstract: Multimodal semantic segmentation has shown great potential in leveraging complementary information across diverse sensing modalities. However, exist

researcharxiv-cs-cv

CRPS-LAM: Probabilistic Regional Weather Forecasting with Continuous Ranked Probability Score

arXiv:2510.09484v3 Announce Type: replace Abstract: Limited-Area Models (LAMs) enable weather forecasting over regional domains at higher resolutions than what is computationally feasible for global m

Hardware

CSAR: Containerized System Architecture for Robotics

arXiv:2606.30293v1 Announce Type: new Abstract: Robotic applications increasingly rely on distributed computational infrastructures that combine embedded devices, edge servers, and cloud resources. Th

hardwarearxiv-cs-ro

CubifyGS: Object-Centric 3D Gaussian Splatting for Lifelong Dynamic Scene Maintenance

model-releasesarxiv-cs-ro

arXiv:2606.28720v1 Announce Type: new Abstract: Lifelong scene mapping under rigid object rearrangement remains a fundamental challenge in robotics. While 3D Gaussian Splatting (3DGS) enables high-fid

Curvature-Guided Sheaf Diffusion for Unsupervised Community Detection on Heterophilic Graphs

arXiv:2606.30249v1 Announce Type: cross Abstract: Detecting communities in heterophilic graphs -- where connected nodes often belong to different classes -- is hard for unsupervised methods: classical

Curvature-Weighted Gradient Diversity: A Noise Measure for Geometry-Adaptive SGD Schedules

model-releasesarxiv-cs-lg

arXiv:2606.30455v1 Announce Type: new Abstract: The standard convergence analysis of mini-batch stochastic gradient descent (SGD) models gradient noise using a single variance term that treats all par

Customized Generative AI Agent for Transportation Engineering Practice: A Development and Continued Pre-training Guideline

arXiv:2606.29014v1 Announce Type: new Abstract: Recent advancements in generative artificial intelligence (AI) and large language models (LLMs) have shown significant promise in automating complex rea

CW-B: Class Weighted Boosting Framework for Imbalance Resilient Multi Class Cardiac Phenotyping

arXiv:2606.29907v1 Announce Type: cross Abstract: Cardiac discharge phenotyping informs post-discharge treatment and follow-up, but real-world records are often incomplete and class-imbalanced, increa

applicationsarxiv-cs-ai

Cybersecurity is the True Frontier for Generative AI Success or Failure

arXiv:2606.28929v1 Announce Type: cross Abstract: Cybersecurity is a real-life test-bed for many machine learning problems at once, especially when considering modern strides in using Large Language M

CylindTrack: Depth-Aware Cylindrical Motion Modeling for Panoramic Multi-Object Tracking

model-releasesarxiv-cs-cv

arXiv:2606.30097v1 Announce Type: new Abstract: Multi-Object Tracking (MOT) is a core capability for embodied perception, and panoramic cameras are attractive for embodied systems because their 360{eg

Tutorials

CytoCLIP: Learning Cytoarchitectural Characteristics in Developing Human Brain Using Contrastive Language Image Pre-Training

arXiv:2601.12282v2 Announce Type: replace-cross Abstract: The functions of different regions of the human brain are closely linked to their distinct cytoarchitecture, which is defined by the spatial a

tutorialsarxiv-cs-ai

D^{2}R^{2}OSR: Degradation-Disentangled Representation for Real-World Omnidirectional Image Super-Resolution

arXiv:2606.29314v1 Announce Type: new Abstract: With the growing demand for immersive visual experiences, high-quality omnidirectional images (ODIs) have become increasingly important. However, limita

applicationsarxiv-cs-cv

Agents

DAIN: Dynamic Agent-Based Interaction Network for Efficient and Collaborative Multimodal Reasoning

arXiv:2606.30189v1 Announce Type: new Abstract: Current multimodal fusion approaches, particularly those based on static Mixture-of-Experts (MoE) architectures, often struggle to provide the adaptive

agentsarxiv-cs-cl

Tutorials

DAPS++: Rethinking Diffusion Inverse Problems with Decoupled Posterior Annealing

arXiv:2511.17038v4 Announce Type: replace Abstract: From a Bayesian perspective, score-based diffusion solves inverse problems through joint inference, embedding the likelihood with the prior to guide

tutorialsarxiv-cs-ai

Data and Evaluation Closed-Loop for Model Capability Enhancement

arXiv:2606.28471v1 Announce Type: new Abstract: Model capability is the central variable in LLM pre-training, yet is never observed directly: data shapes it prospectively, while evaluation reveals it

Data-Driven Energy-Based Learning via Gibbs Measures on Hierarchical Structures

model-releasesarxiv-cs-lg

arXiv:2606.30064v1 Announce Type: new Abstract: We introduce a data-driven probabilistic framework for learning systems based on Gibbs measures on hierarchical structures. Unlike standard empirical ri

Local Ai

Data-Driven Modeling and Control for Tethered Space Systems with Koopman-Informed Graphs

arXiv:2606.29825v1 Announce Type: new Abstract: Modeling tethered space systems is critical for advanced orbital operations. Flexible components such as tethers and space nets are integral to these sy

local-aiarxiv-cs-ro

Data-Efficient Multimodal Alignment for Histopathology-based Molecular Prediction

arXiv:2606.29949v1 Announce Type: cross Abstract: H&E-stained whole-slide images offer cohort-scale availability and rich spatial context but lack molecular specificity, whereas bulk RNA-seq provides

safetyarxiv-cs-ai

Data Provenance for Image Auto-Regressive Generation

arXiv:2606.28386v1 Announce Type: cross Abstract: Image autoregressive models (IARs) have recently demonstrated remarkable capabilities in visual content generation, achieving photorealistic quality a

Database Context Compression for Text-to-SQL on Real-World Large Databases

arXiv:2606.28601v1 Announce Type: cross Abstract: Recent progress in Text-to-SQL has been driven by stronger language models and prompting strategies, yet performance on real enterprise benchmarks suc

DataComp-VLM: Improved Open Datasets for Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2606.28551v1 Announce Type: cross Abstract: Building performant Vision-Language Models (VLMs) requires carefully curating large-scale training datasets, yet the community lacks systematic benchm