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Comparative Evaluation of Machine Learning and Deep Learning Models for Wound-Rotor Synchronous Motor Performance Prediction

arXiv:2606.21230v1 Announce Type: new Abstract: Wound rotor synchronous motors have emerged as a strong alternative that eliminates dependence on REEs. However, WRSM design requires the simultaneous o

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Compress the Easy, Explore the Hard: Difficulty-Aware Entropy Regularization for Efficient LLM Reasoning

DGX agent

arXiv:2602.22642v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) has substantially empowered Large Language Models (LLMs) to tackle complex reasoning tasks, yet the verbose nature of explici

applicationsarxiv-cs-lg

23 Jun 2026

Agents

Compressing Observation History into Agent Memory: Distilling Transformers into Recurrent Transformers

arXiv:2606.21562v1 Announce Type: new Abstract: Transformers are AI's workhorse with strong performance in modeling sequential data, but their computational cost becomes prohibitive when processing lo

agentsarxiv-cs-cv

Compression and Retrieval: Implicit Memory Retrieval for Video World Models

arXiv:2606.23105v1 Announce Type: new Abstract: Video world models hold promise for simulating interactive environments, yet maintaining consistent long-term memory across complex camera trajectories

Concept Alignment Contrast and Long-Short Prompt Memory for Test-Time Adaptation of SAM3 in Medical Image Segmentation

arXiv:2606.22963v1 Announce Type: new Abstract: Concept segmentation models like Segment Anything Model 3 (SAM3) show strong generalization on natural images, yet their performance degrades in medical

Concept-Constrained Prompt Learning for Few-Shot CLIP Adaptation

arXiv:2606.22567v1 Announce Type: new Abstract: Few-shot prompt learning is an effective strategy for adapting CLIP to downstream tasks, but class-only prompt optimization can overfit base-class super

Conceptual Design of an Ecosystem for Real Farm Data Collection toward Agricultural AI Foundation Models

arXiv:2606.23258v1 Announce Type: new Abstract: Data scarcity is a fundamental challenge in developing AI and foundation models for agricultural robots. Existing open-source data platforms do not prov

researcharxiv-cs-ro

Hardware

Concordia: JIT-Compiled Persistent-Kernel Checkpointing for Fault-Tolerant LLM Inference

arXiv:2606.23521v1 Announce Type: cross Abstract: Long-running LLM agents keep valuable state resident on GPUs: KV caches, request schedulers, communication state, and sometimes online adapters. Losin

hardwarearxiv-cs-lg

Conditional Flow Matching for Visually-Guided Acoustic Highlighting

arXiv:2602.03762v3 Announce Type: replace-cross Abstract: Visually-guided acoustic highlighting seeks to rebalance audio in alignment with the accompanying video, creating a coherent audio-visual expe

Conditional neural control variates for variance reduction in Bayesian inverse problems

arXiv:2602.21357v2 Announce Type: replace-cross Abstract: Bayesian inference for inverse problems involves computing expectations under posterior distributions--e.g., posterior means, variances, or pr

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis

arXiv:2602.11973v2 Announce Type: replace Abstract: In critical decision support systems based on medical imaging, the reliability of AI-assisted decision-making is as relevant as predictive accuracy.

Confidently Wrong: Severity-Aware Calibration of Prompt-Injection Detectors under Attack Shift

arXiv:2606.22659v1 Announce Type: cross Abstract: Prompt-injection detectors are deployed as guards: a model scores an input and a downstream system trusts or blocks it on that score. I study the conf

Local Ai

Configurable Algorithms for Histopathologic Cancer Detection on Quantum Hardware

arXiv:2606.21752v1 Announce Type: cross Abstract: Histopathologic cancer detection is challenging due to tissue variability, staining differences, and subtle visual distinctions between disease classe

local-aiarxiv-cs-cv

Conflict-Aware Switching for CBF-CLF-Based Multi-Goal Navigation

arXiv:2606.21577v1 Announce Type: new Abstract: Quadratic programs (QPs) using Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs) are widely used for safe control in reach-and-avoi

safetyarxiv-cs-ro

Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces

arXiv:2507.15741v2 Announce Type: replace-cross Abstract: This paper introduces a framework for uncertainty quantification in regression models defined on metric spaces. Using a proposed notion of hom

ConnectomeBench2: A Unified Benchmark for Automated Connectomic Proofreading

arXiv:2606.21116v1 Announce Type: new Abstract: Proofreading--correcting segmentation errors in 3D brain reconstructions--is the rate-limiting step in synapse-resolution connectomics. We release Conne

Applications

Context-Aware Autoregressive Diffusion for Gloss-Wise Sign Language Production

arXiv:2606.21234v1 Announce Type: new Abstract: To generate natural and accurate sentence-level sign language, synthesizing the 'gloss', the fundamental semantic unit, is essential. However, most curr

applicationsarxiv-cs-cv

Continuous Behavioral Authentication via Multi-Expert BERT Log Analysis for Secure Data Sharing

arXiv:2606.21900v1 Announce Type: cross Abstract: Continuous authentication for mobile and zero-trust systems requires nonintrusive evidence confirming the enrolled user-device context remains valid a

Continuous-Time Probabilistic Correctors for Uncertainty-Aware Physics-Based Spacecraft Trajectory Forecasting

arXiv:2606.21021v1 Announce Type: new Abstract: Long-horizon spacecraft trajectory forecasting suffers from error accumulation due to the absence of corrective observations in the forecast regime, mak

Tutorials

Contrastive and Adaptive Multi-modal Masked Autoencoder for Spatial Transcriptomics

arXiv:2606.21156v1 Announce Type: new Abstract: The high cost of spatial transcriptomics (ST) has driven extensive studies into predicting gene expression directly from H&E histology images. However,

tutorialsarxiv-cs-cv

Controllable Texture Tiling with Transformed RoPE-Enhanced Diffusion Models

arXiv:2606.22945v1 Announce Type: cross Abstract: Realistic integration of user-specified textures into scene images is a fundamental task in computer graphics and image editing. While existing materi

Convergence Analysis of Nystrom Subsampling in Covariate Shift Adaptation for Misspecified case

arXiv:2606.22259v1 Announce Type: cross Abstract: This paper investigates convergence properties of regularized Nystrom subsampling applied to the unsupervised domain adaptation problem under covariat

Convergence of Gradient Descent for General Neural Network Architectures Beyond the NTK Regime

arXiv:2606.23364v1 Announce Type: new Abstract: Training dynamics is central to understanding neural networks, yet its theoretical analysis remains difficult even for simple architectures and becomes

Convergence Rate Analysis of LION

arXiv:2411.07724v2 Announce Type: replace Abstract: The LION (evoLved sIgn mOmeNtum) optimizer for deep neural network training was found by Google via program search, with the simple sign update yet

Agents

Cooperative-ORCA*: Real-Time Proactive Deadlock Avoidance for Continuous-Space Multi-Agent Navigation

arXiv:2606.22757v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) is a problem that requires computing collision-free paths for a set of agents from their start locations to designated g

agentsarxiv-cs-ro

CoorDex: Coordinating Body and Hand Priors for Continuous Dexterous Humanoid Loco-Manipulation

arXiv:2606.23680v1 Announce Type: cross Abstract: Humanoid loco-manipulation is often simplified into a stop-and-go process: walking to an object, stopping to manipulate it, and then resuming locomoti

CoRDE: Concept-Prior Routed Diffusion Experts for Structural Generalization in Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.21935v1 Announce Type: new Abstract: Diffusion models excel at capturing multi-modal action distributions in robot imitation learning. However, in multi-task and long-horizon scenarios, mon

CoSA: Correlation-Guided Change Attention with Learnable Residual Gating for Remote Sensing Change Detection

arXiv:2606.21932v1 Announce Type: new Abstract: Remote sensing change detection (CD) from bi-temporal imagery is critical for applications such as urban monitoring, disaster assessment, and environmen

Counsel: A Meta-Evaluation Dataset for Agentic Tasks

arXiv:2606.21627v1 Announce Type: cross Abstract: As agentic systems tackle increasingly complex multi-step tasks, evaluating their trajectories presents a major bottleneck - human annotation of a sin

Counterfactual learning of new adaptive instructional policies using logged data

arXiv:2606.23015v1 Announce Type: new Abstract: Optimizing instructional policies in Intelligent Tutoring Systems (ITS) typically requires costly online experimentation or student simulators that may

Coupled Routing and Configuration Optimization for Multi-Viewpoint Robotic Inspection

arXiv:2606.20739v1 Announce Type: new Abstract: We present a unified framework that turns a set of 6-DoF inspection viewpoints into a time-optimal, collision-free route for a 9-DoF robotic system. Unl

researcharxiv-cs-ro

CourseBlueprint: A Structured Pipeline for Adaptive Pedagogical Video Generation Grounded in Course Corpora

arXiv:2606.20608v1 Announce Type: cross Abstract: Generative text-to-video systems can produce visually fluent educational clips, but they rarely encode the pedagogical content knowledge (PCK) needed

Local Ai

CoVStream: Edge-Cloud Collaboration for Understanding of Long Video Streams

arXiv:2606.22804v1 Announce Type: new Abstract: Long, continuous video streams are an increasingly critical driver of multimedia intelligence. Existing efforts often handle long videos with a sample-e

local-aiarxiv-cs-cv

CQD-SHAP: Explainable Complex Query Answering via Shapley Values

arXiv:2510.15623v2 Announce Type: replace Abstract: Complex query answering (CQA) goes beyond the widely studied link prediction task by addressing more sophisticated queries that require multi-hop re

CRAX: Fast Safe Reinforcement Learning Benchmarking

arXiv:2606.20376v2 Announce Type: replace Abstract: Safety is a core concern for deploying reinforcement learning (RL) agents in real-world domains such as robotics and autonomous driving. While bench

CrediBench: Building Web-Scale Network Datasets for Information Integrity

arXiv:2509.23340v4 Announce Type: replace-cross Abstract: Automatically assessing the credibility of online sources presents an invaluable tool for navigating today's information ecosystem. However, e

Cross-Modal Corroboration for Annotation-Free Wildlife Monitoring

arXiv:2606.21613v1 Announce Type: new Abstract: Scaling wildlife monitoring for real-world conservation deployments requires automated analysis of smart sensors that operate under severe annotation sc

Cross-View Yaw Estimation in Location Uncertainty with Line-Aligning Yaw Scoring

arXiv:2606.22094v1 Announce Type: new Abstract: Accurate yaw estimation is a bottleneck in cross-view localization between ground view and Bird's Eye View (BEV). Existing methods couple yaw with trans

Local Ai

CuDi: Curve Distillation for Efficient and Controllable Exposure Adjustment

arXiv:2207.14273v2 Announce Type: replace Abstract: We present Curve Distillation, CuDi, for efficient and controllable exposure adjustment without the requirement of paired or unpaired data during tr

local-aiarxiv-cs-cv

Cultural Counterfactuals: Evaluating Cultural Biases in Large Vision-Language Models with Counterfactual Examples

arXiv:2603.02370v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) have grown increasingly powerful in recent years, but can also exhibit harmful biases. Prior studies investigat

CuratorKIT : Data Curation and Synthetic Data Generation for LLM Post-Training

arXiv:2606.21631v1 Announce Type: cross Abstract: Data curation is a critical part of post-training pipelines for large language models, yet existing tools often treat ingestion, deduplication, synthe

Curriculum Reinforcement Learning Can Incentivize Reasoning Capacity in LLMs Beyond the Base Model

arXiv:2606.22317v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is widely viewed as a promising path toward continuously improving large language models. Recent w

Agents

Curvature-Adaptive Consistency Flow Matching: Autonomous Trajectory Optimization via Reinforcement Learning

arXiv:2606.22394v1 Announce Type: new Abstract: Consistency distillation has significantly accelerated the inference of diffusion models. In this work, we reveal an intriguing asymmetry: while Logit-N

agentsarxiv-cs-cv

Curvature-aware 3D length estimation of greenhouse cucumbers using RGB-D imaging and cubic spline arc-length integration

arXiv:2606.22439v1 Announce Type: new Abstract: Commercial greenhouse cucumber production is graded by fruit length, which drives harvest scheduling, labour allocation, and logistics. Manual measureme

Tutorials

CurvSegFlow: Time-Conditioned Flow Matching for Robust Segmentation of Curvilinear Structures in Noisy Biomedical Images

arXiv:2606.21608v1 Announce Type: new Abstract: Accurate segmentation of curvilinear structures remains challenging in biomedical imaging due to their thin geometry, complex topology, and sensitivity

tutorialsarxiv-cs-cv

Customizing Video Portraits via Identity-ActionDecoupling

arXiv:2606.22347v1 Announce Type: new Abstract: Identity-Preserving Text-to-Video Generation (IPT2V) seeks to synthesize a temporally coherent video from a reference image and a textual description, w

CVSBench: A Comprehensive Benchmark for Cross-view Spatial Reasoning and Dreaming

arXiv:2606.22476v1 Announce Type: new Abstract: Humans can effortlessly reason about scenes across different viewpoints, yet it remains unclear whether Vision-Language Models (VLMs) possess similar cr

D2HDMap: Non-visible Driveline Map Prior for Online Vectorized HD Map Prediction

arXiv:2606.20725v1 Announce Type: new Abstract: Accurate, up-to-date representations of road structures are critical for the safe operation of autonomous vehicles. Existing systems rely either on cost