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Cell as Point: One-Stage Framework for Efficient Cell Tracking

arXiv:2411.14833v4 Announce Type: replace-cross Abstract: Conventional multi-stage cell tracking approaches rely heavily on detection or segmentation in each frame as a prerequisite, requiring substan

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CenSynCMB: Centre Maps and Physics-Guided Synthesis for Microbleed Detection

DGX agent

arXiv:2607.05325v1 Announce Type: new Abstract: Cerebral microbleeds (CMBs) are MRI markers of small vessel disease and the microbleed component of amyloid related imaging abnormalities (ARIA-H), but

researcharxiv-cs-cv

7 Jul 2026

CertMix: Certified, Data-Efficient Metamaterial Design by Affine Mixing of Aligned Neural-Implicit Weight Spaces

arXiv:2607.04123v1 Announce Type: new Abstract: Inverse design of mechanical metamaterials seeks a periodic unit cell whose homogenized elastic properties meet a prescribed target, but current learnin

CGGS: Consistency-Augmented Geometric Gaussian Splatting for Ego-centric 3D Scene Generation

arXiv:2607.03819v1 Announce Type: cross Abstract: Challenges remain in ego-centric 3D scene generation due to limited view overlap and the dominant influence of individual perspectives on scene interp

researcharxiv-cs-ai

ChainReaction: Causal Chain-Guided Reasoning for Modular and Explainable Causal-Why Video Question Answering

arXiv:2508.21010v3 Announce Type: replace-cross Abstract: Existing Causal-Why Video Question Answering (VideoQA) models often struggle with higher-order reasoning, relying on opaque, monolithic pipeli

researcharxiv-cs-ai

Channel-Adaptive Robust Aggregation for Over-the-Air Federated Learning in Heterogeneous Networks

arXiv:2607.04218v1 Announce Type: new Abstract: The growing demand for privacy-preserving, data-intensive applications such as IoT, augmented reality, and autonomous systems positions Federated Learni

safetyarxiv-cs-lg

Characterizing the Temporal, Emotional, and Social Patterns of Adolescent Substance Use Discussions on Reddit

arXiv:2607.04566v1 Announce Type: new Abstract: Adolescence is a critical developmental period marked by heightened emotional sensitivity, social stress, and vulnerability to substance use. However, t

researcharxiv-cs-cl

Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models

model-releasesarxiv-cs-cl

arXiv:2506.07468v4 Announce Type: replace-cross Abstract: Conventional large language model (LLM) safety alignment relies on a reactive, disjoint loop: attackers exploit a static model, then defenders

ChatImage: Navigating Long-Form LLM Answers through Interactive Images

arXiv:2607.05290v1 Announce Type: new Abstract: Large Language Models (LLMs) can produce detailed answers to complex queries, but these answers are typically presented as dense linear text, which make

Choosing a parallel heterogeneous ensemble method for tabular classification

arXiv:2607.05103v1 Announce Type: new Abstract: Parallel ensemble methods were compared on 56 small-to-medium tabular classification tasks drawn from OpenML CC18. A set of ``best practice'' recommenda

Chronos: The AI Co-Historian

arXiv:2604.03553v2 Announce Type: replace Abstract: AI is increasingly supporting, accelerating, and automating scientific discovery across subjects. Yet, the adoption of AI in historical research rem

CineMobile: On-Device Image-to-Video Diffusion for Cinematic Camera Motion Generation

arXiv:2607.03803v1 Announce Type: cross Abstract: The growing demand for image-to-video creation on mobile devices has increasingly focused on cinematic motion effects like bullet time, dolly zoom, sl

CIPHER: Causal Intervention Pathways for Healthcare Equity and Robustness

arXiv:2607.02596v1 Announce Type: new Abstract: Deep learning models for medical diagnosis frequently exhibit substantial performance disparities across sensitive subgroups (e.g., race, sex), even whe

applicationsarxiv-cs-cv

City landscape in sight: A crowdsourced framework for unlocking urban-scale window view perceptions from real estate imagery

arXiv:2606.15198v2 Announce Type: replace Abstract: City landscapes viewed through home windows influence quality of life, yet perceptions of actual window views at the urban scale remain understudied

City-Level 3D Surface Reconstruction with Viewpoint Orientation Partitioning and Scene Completion

arXiv:2607.03771v1 Announce Type: new Abstract: Multi-view 3D surface reconstruction is a longstanding challenge in computer vision. Although recent large-scale reconstruction methods based on 3D Gaus

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection

arXiv:2607.02930v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) excel in diverse vision tasks, but full-parameter retraining is computationally expensive as real-world knowled

CLABTOOLKIT: An Open-Source Toolkit for Routine Processing, Manipulation, and Visualization of Neuroimaging Data

arXiv:2607.02638v1 Announce Type: new Abstract: Neuroimaging research requires manipulating heterogeneous data structures, including raw MRI volumes, volumetric parcellations, cortical surface meshes,

Claim-Level Rubric Rewards for Video Caption Reinforcement Learning

arXiv:2607.05150v1 Announce Type: new Abstract: In this paper, we introduce Claim-Level Rubric Rewards (CuRe), a structured reward framework designed to address the reward-design bottleneck in reinfor

safetyarxiv-cs-cv

CLARITY: Medical World Model for Guiding Treatment Decisions by Modeling Context-Aware Disease Trajectories in Latent Space

arXiv:2512.08029v3 Announce Type: replace-cross Abstract: Clinical decision-making in oncology requires predicting dynamic disease evolution, a task current static AI predictors cannot perform. While

ClassicLogic: A Knowledge-Driven Benchmark of Classic Puzzle Games for Evaluating Compositional Generalization

arXiv:2607.05185v1 Announce Type: new Abstract: Compositional generalization, the ability to understand and produce novel combinations of known components, remains a fundamental challenge for modern a

Classroom Behavior Monitoring with YOLO An Empirical Study in Higher Education Settings

arXiv:2607.02580v1 Announce Type: new Abstract: Classroom behavior monitoring plays a vital role in evaluating student engagement and improving teaching effectiveness. Traditional observation methods

applicationsarxiv-cs-cv

CLEANER: Self-Purified Trajectories Boost Agentic Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2601.15141v2 Announce Type: replace Abstract: Agentic Reinforcement Learning (RL) has empowered Large Language Models (LLMs) to utilize tools like Python interpreters for complex problem-solving

CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk

arXiv:2507.08150v4 Announce Type: replace-cross Abstract: Accurate uncertainty quantification is critical for reliable predictive modeling. Existing methods typically address either aleatoric uncertai

applicationsarxiv-cs-lg

CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving

arXiv:2607.02841v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E-AD) aims to directly map raw sensor information to driving actions. Recently, with the rapid advancement of multi-m

safetyarxiv-cs-cv

ClinOCR-Bench: A Comprehensive Clinical Scanned Document Dataset for Optical Character Recognition Model Evaluation

arXiv:2607.03650v1 Announce Type: cross Abstract: Extracting textual information from scanned medical documents, such as external laboratory reports and manually filled forms, has been a major challen

Closed-loop vs. Open-loop Kalman Filter Architectures in Airborne Aided Inertial Navigation

arXiv:2607.03338v1 Announce Type: new Abstract: Closed-loop (or feedback) error-state Kalman filters with their relatives and offspring are the state-of-the-art in modern aided inertial navigation res

safetyarxiv-cs-ro

Closing Gaps in Emissions Monitoring with Climate TRACE

arXiv:2511.19277v2 Announce Type: replace Abstract: Global greenhouse gas emissions estimates are essential for monitoring and mitigation planning. Existing emissions datasets provide critical foundat

Closing the Reality Gap: Zero-Shot Sim-to-Real Deployment for Dexterous Force-Based Grasping and Manipulation

arXiv:2607.04940v1 Announce Type: new Abstract: Human-like dexterous hands with multiple fingers offer human-level manipulation capabilities but remain difficult to train the control policies that can

applicationsarxiv-cs-ro

CN-CBF: Composite Neural Control Barrier Function for Robot Navigation in Dynamic Environments

arXiv:2603.06921v2 Announce Type: replace-cross Abstract: Safe navigation of autonomous robots remains one of the core challenges in the field, especially in dynamic and uncertain environments. One pr

safetyarxiv-cs-lg

Co-Adaptive Multi-Task LoRA: Transfer-Aware, Label-Free Control of Domain Participation

arXiv:2607.03522v1 Announce Type: new Abstract: Fine-tuning a single low-rank adapter on many domains at once is multi-task learning: the domains must be co-learned, and how they share the adapter dec

CoACT: Action-Preserving Observation Compression for Coding Agents

arXiv:2607.02911v1 Announce Type: cross Abstract: LLM-based coding agents solve software-engineering tasks through iterative interactions with development environments, where returned observations acc

agentsarxiv-cs-ai

Code Benchmarks Should Prioritize Rigor, Reliability, and Reproducibility

arXiv:2501.10711v5 Announce Type: replace-cross Abstract: Code-related benchmarks play a critical role in evaluating large language models (LLMs), yet their quality fundamentally shapes how the commun

CodeJeNN: A simple C++ neural network generator for physics applications

arXiv:2607.02746v1 Announce Type: cross Abstract: Machine learning has shown speedups for numerical methods in physics applications, but integrating Python-based libraries into high-performance C++ so

CoDoL: Conditional Domain Prompt Learning for Out-of-Distribution Generalization

arXiv:2509.15330v2 Announce Type: replace Abstract: Recent advances in pre-training vision-language models (VLMs), e.g., contrastive language-image pre-training (CLIP) methods, have shown great potent

safetyarxiv-cs-cv

CoFEND: A Cross-Modal Fusion End-to-End Network for Cold-Start Drug-Drug Interaction Prediction

arXiv:2607.02928v1 Announce Type: new Abstract: Cold-start drug-drug interaction (DDI) prediction for new drugs is critical for minimizing unexpected adverse drug reactions. The key challenge is to ca

CoGen3D: An Agentic Human-AI Co-Design Pipeline for 3D Asset Generation for Virtual Reality

arXiv:2607.03731v1 Announce Type: cross Abstract: Creating 3D assets for virtual reality requires modeling expertise, which restricts the authorship of immersive experiences. Existing generative AI to

agentsarxiv-cs-ai

CogRad: A Cognitively-Inspired Multi-Agent Framework for Radiology Report Generation

arXiv:2607.03853v1 Announce Type: new Abstract: Automated radiology report generation (RRG) can ease radiologist workload, yet most existing systems produce a report in a single forward pass, with no

agentsarxiv-cs-cv

Cohort-attention Evaluation Metrics for Tied Data

arXiv:2503.12755v3 Announce Type: replace Abstract: Artificial intelligence (AI) has significantly improved medical screening accuracy, particularly in cancer detection and risk assessment. However, t

safetyarxiv-cs-lg

Tutorials

CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion

arXiv:2607.05046v1 Announce Type: new Abstract: Evaluating generative AI models is a routine, but resource-intensive, process that is conducted over and over again during the course of model developme

tutorialsarxiv-cs-lg

Combining Discrepancy-Confusion Uncertainty and Calibration Diversity for Active Fine-Grained Image Classification

arXiv:2509.24181v2 Announce Type: replace Abstract: Active learning (AL) aims to build high-quality labeled datasets by iteratively selecting the most informative samples from an unlabeled pool under

Tutorials

COMET: Combinatorial Optimization for Multiplex Editing Targets Via Constraint-Preserving QAOA

arXiv:2607.02622v1 Announce Type: cross Abstract: Multiplex CRISPR-Cas9 gene editing requires selecting one guide RNA per target gene subject to cross-gene interactions: a constrained combinatorial pr

tutorialsarxiv-cs-ai

CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents

arXiv:2607.05378v1 Announce Type: new Abstract: Long-horizon agentic LLMs are increasingly limited by finite context windows, as extended interaction trajectories can exceed the maximum context length

agentsarxiv-cs-lg

Comparison of Loss Functions for Robust Deep Learning-based Echocardiography Segmentation when Learning with Partially Labelled Data from Multiple Domains

arXiv:2607.05008v1 Announce Type: cross Abstract: Echocardiography is the first imaging modality used for assessing cardiac function, and accurate segmentation of cardiac structures is essential for d

researcharxiv-cs-ai

Complexity of Normalized Persistence Problems for Topological Data Analysis and Local Hamiltonians

arXiv:2607.03278v1 Announce Type: cross Abstract: Topological data analysis (TDA) is a machine learning technique that uses topology to extract patterns from data and has shown the potential to exhibi

ComplexMimic: Human-Scene Interaction Imitation in Complex 3D Environments

arXiv:2607.02034v2 Announce Type: replace Abstract: Physics-based Human-Scene Interaction (HSI) imitation learning is crucial for embodied intelligence as it bridges the gap between kinematic 3D motio

CompLLM: Compression for Long Context Q&A

arXiv:2509.19228v2 Announce Type: replace Abstract: Large Language Models (LLMs) face significant computational challenges when processing long contexts due to the quadratic complexity of self-attenti

applicationsarxiv-cs-cl

Compositional Generalization Requires Linear, Orthogonal Representations in Vision Embedding Models

arXiv:2602.24264v2 Announce Type: replace Abstract: Compositional generalization, the ability to recognize familiar parts in novel contexts, is a defining property of intelligent systems. Although mod

Compressed Computation under L^4 Loss is likely Computation in Superposition

arXiv:2607.04800v1 Announce Type: new Abstract: Neural networks are thought to represent concepts as directions in their activation space, and superposition lets them encode more concepts than they ha