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CoorGrasp: Coordinated Contact Control for Adaptive Dexterous Grasping Under Uncertainty

arXiv:2607.03557v1 Announce Type: new Abstract: While recent research has focused heavily on dexterous grasp pose generation, less attention has been devoted to the execution of planned grasps. Under

applicationsarxiv-cs-ro

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Local Ai

CORA: Generalizable coronary artery disease assessment and risk stratification from coronary CT angiography using pathology-centric representation learning

DGX agent

arXiv:2603.24847v2 Announce Type: replace Abstract: Coronary artery disease, a leading cause of cardiovascular mortality worldwide, can be assessed non-invasively by coronary computed tomography angio

local-aiarxiv-cs-cv

7 Jul 2026

CORA: Per-Slice Coherent Orthogonal Rotation for SVD-based Low-Rank Adaptation

model-releasesarxiv-cs-lg

arXiv:2607.02576v1 Announce Type: cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) commonly adapts pretrained weights through low-rank updates, and recent methods further exploit the singular va

CoRE-VLA: Towards Scalable and Robust Vision-Language-Action Modeling via Conditional Routing of Experts

arXiv:2607.03693v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced generalist robotic manipulation, yet real-world deployment reveals a fundamental challenge: robots are

safetyarxiv-cs-ro

Correlation-Weighted Multi-Reward Optimization for Compositional Generation

arXiv:2603.18528v2 Announce Type: replace Abstract: Text-to-image models produce images that align well with natural language prompts, but compositional generation has long been a central challenge. M

researcharxiv-cs-ai

Agents

Cortex: A Bidirectionally Aligned Embodied Agent Framework for Long-horizon Manipulation

arXiv:2607.05377v1 Announce Type: cross Abstract: While recent Vision-Language-Action (VLA) models show promise toward generalist manipulation policies, they struggle with long-horizon tasks due to th

agentsarxiv-cs-ai

Counterfactual Methods for Detecting Unfairness in Anti-Money Laundering Algorithms

arXiv:2607.05101v1 Announce Type: new Abstract: The application of machine learning-based predictive algorithms to Anti-Money Laundering (AML) has grown rapidly, driven by the vast volume of financial

safetyarxiv-cs-lg

Counterfactual Operator Relevance for PDE Discovery: Screening, Pruning, and Identifiability

arXiv:2506.20181v2 Announce Type: replace Abstract: We study operator relevance in data-driven partial differential equation (PDE) discovery. Sparse residual methods can select terms that improve resi

Coverage-Controlled Preference Mining from Noisy Claim Verification for Evidence-Grounded Generation

arXiv:2603.10494v2 Announce Type: replace Abstract: Evidence-grounded generation produces summaries whose claims should be supported by supplied evidence, but claim-level verifiers provide noisy feedb

safetyarxiv-cs-cl

Covert Trait Propagation Is Representation Alignment: Mechanistic Evidence from Hidden-Channel Distillation

arXiv:2607.04432v1 Announce Type: cross Abstract: A student model trained on pure uniform noise can still inherit its teacher's digit-classification ability, provided the two share initialization. Pre

CP-WSP: A Declarative CP-SAT Framework for Configurable Multi-Constraint Workforce Scheduling

arXiv:2607.05177v1 Announce Type: new Abstract: Workforce scheduling is an NP-hard combinatorial optimization problem requiring simultaneous satisfaction of labor regulations, coverage requirements, e

Hardware

CPR: Chained Perceptual Refinement for Coarse-to-Fine Medical Image Classification

arXiv:2607.02591v1 Announce Type: new Abstract: High resolution medical images contain fine grained, spatially sparse cues that are critical for diagnosis, yet preserving full resolution incurs substa

hardwarearxiv-cs-cv

Agents

CRISP: A Spatiotemporal Camera-Radar Backbone for Driving via Forecasting-Based World-Model Pretraining

arXiv:2607.04541v1 Announce Type: cross Abstract: Camera-radar (CR) fusion is a practical sensing configuration for autonomous driving, but existing models are typically trained with task-specific sup

agentsarxiv-cs-ai

Criterion-Conditional In-Context Learning: Evaluating Criterion-Shift Adaptation in Vision-Language Models

arXiv:2607.02575v1 Announce Type: cross Abstract: Vision-language models can perform new tasks without parameter updates through in-context learning (ICL), whose core mechanism is utilizing the suppor

CritiqueDriveVLM: From Verifier-Guided Reinforcement Learning to Latent Thought Distillation for Autonomous Driving

arXiv:2607.04179v1 Announce Type: cross Abstract: End-to-end Vision-Language Models (VLMs) show immense potential in autonomous driving. However, standard Supervised Fine-Tuning (SFT) often suffers fr

CRODA-ST: Single-Target Cross-Receiver Open-Set Radio Fingerprint Recognition

arXiv:2607.02567v1 Announce Type: cross Abstract: Radio frequency fingerprint identification (RFFI) provides a physical-layer credential for Internet of Things devices, but open-set decisions become f

Cross-device Collaborative Test-time Adaptation with Zeroth-order Optimization and Model Merging

arXiv:2607.02988v1 Announce Type: new Abstract: Test-time adaptation (TTA) mitigates domain shifts by using incoming test data to update a model on the fly. The majority of TTA methods require resourc

applicationsarxiv-cs-cv

Cross-Embodiment Robot Manipulation via a Unified Hand Action Space

arXiv:2607.03570v1 Announce Type: new Abstract: Robot manipulation policies are typically tied to specific robotic hand embodiments, limiting the transfer of learned behaviors across platforms with di

safetyarxiv-cs-ro

Cross-Modal Fusion of OCT and OCT angiography enface for Improved Diagnostics of Diabetic Retinopathy

arXiv:2607.03959v1 Announce Type: cross Abstract: Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, highlighting the need for accurate and accessible screening tools. Optica

researcharxiv-cs-cv

CrossHallu: Do Hallucination Signals Generalize Across Languages and Domains in Large Language Model's Internals?

arXiv:2607.04029v1 Announce Type: new Abstract: Recent hallucination detection techniques in large language models (LLMs) focus on directly extracting features from a model's internal representations

safetyarxiv-cs-cl

CRRL: A Causality-Based Reinforcement Learning Framework for Autonomous System Recovery

arXiv:2607.03177v1 Announce Type: cross Abstract: Traditional reinforcement learning (RL) for recovery in autonomous systems lacks causal understanding and generalizes poorly to novel failure scenario

CSB: A Counting and Sampling tool for Bit-vectors

arXiv:2607.04142v1 Announce Type: cross Abstract: Satisfiability modulo theory (SMT) solvers have significantly advanced automated reasoning due to their effectiveness in solving problems across vario

researcharxiv-cs-ai

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

model-releasesarxiv-cs-lg

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

CTForensics: A Comprehensive Dataset and Method for AI-Generated CT Image Detection

model-releasesarxiv-cs-cv

arXiv:2603.01878v2 Announce Type: replace Abstract: Recent advances in generative AI have made synthetic Computed Tomography (CT) images increasingly realistic, enabling promising applications in medi

Local Ai

Ctrl-Z Sampling: Scaling Diffusion Sampling with Controlled Random Zigzag Explorations

arXiv:2506.20294v5 Announce Type: replace Abstract: Diffusion models generate conditional samples by progressively denoising Gaussian noise, yet the denoising trajectory can stall at visually plausibl

local-aiarxiv-cs-cv

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

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

Local Ai

Curated retrieval versus open web search in public AI information services: a coverage-trust trade-off

arXiv:2607.05217v1 Announce Type: cross Abstract: Public institutions increasingly use large language models (LLMs) to answer citizens' questions, often pairing a curated knowledge base with live web

local-aiarxiv-cs-cl

CURE: Controllable Unified Image Restoration for Complex Degradations

arXiv:2607.03044v1 Announce Type: new Abstract: The presence of composite degradations poses a significant challenge, since the underlying corruption factors exhibit complex and interdependent interac

researcharxiv-cs-cv

Current as Touch: Proprioceptive Contact Feedback for Compliant Dexterous Manipulation

arXiv:2607.03529v1 Announce Type: new Abstract: Compliance is essential for dexterous manipulation, yet existing solutions often rely on external tactile or force sensors that are costly, fragile, and

safetyarxiv-cs-ro

Curriculum-Guided Layer Scaling for Language Model Pretraining

model-releasesarxiv-cs-cl

arXiv:2506.11389v4 Announce Type: replace Abstract: As the cost of pretraining large language models grows, there is continued interest in strategies to improve learning efficiency during this core tr

CV-DCLR: Causal-Visual Dynamic Label Refinement for Robust Zero-Shot Learning

arXiv:2607.02601v1 Announce Type: new Abstract: Zero-Shot Learning (ZSL) facilitates knowledge transfer via shared semantic spaces. However, a critical bottleneck in this paradigm is Semantic Entangle

safetyarxiv-cs-cv

Dashboard2Code: Evaluating Multimodal Models on Reconstructing Interactive Dashboards

arXiv:2607.04727v1 Announce Type: cross Abstract: Automatic data visualization generation has advanced rapidly with multi-modal large language models, yet existing efforts largely focus on static char

Hardware

Data Driven Optimization of GPU efficiency for Distributed LLM-Adapter Serving

arXiv:2602.24044v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) adapters enable low-cost model specialization, but introduce complex caching and scheduling challenges in distribut

hardwarearxiv-cs-ai

Data-Driven Soft Labeling Scales DNA Read Classification to Whole-Body Cell-Type Deconvolution

arXiv:2607.04987v1 Announce Type: new Abstract: Cell-type deconvolution, the task of estimating the proportions of constituent cell types in a heterogeneous biological sample, is a core problem in com

applicationsarxiv-cs-lg

Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks

arXiv:2603.14830v3 Announce Type: replace Abstract: Dataset distillation, a training-aware data compression technique, has recently attracted increasing attention as an effective tool for mitigating c

DC-Motion: Decoupling Structure and Details via Discrete-Continuous Tokens for Human Motion Generation

arXiv:2606.14721v2 Announce Type: replace-cross Abstract: Text-to-motion generation requires modeling both global action structure and fine-grained motion dynamics from natural language. Existing appr

researcharxiv-cs-cv

Local Ai

Decentralised Federated Learning over Temporal Networks: The Role of Heterogeneities

arXiv:2607.03171v1 Announce Type: cross Abstract: Decentralised federated learning, based on peer-to-peer communication, is increasingly proposed for on-device training of machine learning models, pro

local-aiarxiv-cs-ai

Decentralized Aggregation of LLM Predictions via Wagering Mechanisms

arXiv:2607.04389v1 Announce Type: new Abstract: It is increasingly common to aggregate predictions from multiple LLMs, each with domain expertise or access to private tools and data, to improve collec

Decentralized Federated Learning by Partial Message Exchange

arXiv:2603.01730v2 Announce Type: replace Abstract: Decentralized federated learning (DFL) has emerged as a transformative server-free paradigm that enables collaborative learning over large-scale het

Decomposed Prompting Does Not Fix Knowledge Gaps, But Helps Models Say 'I Don't Know'

arXiv:2602.04853v2 Announce Type: replace Abstract: Large language models often struggle to recognize their knowledge limits in closed-book question answering, leading to confident hallucinations. Whi

safetyarxiv-cs-cl

Decomposition for Bayesian Networks: Local and Parallel Inference

model-releasesarxiv-cs-lg

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

Deep Generative Spatiotemporal Engression for Probabilistic Forecasting of Epidemics

arXiv:2603.07108v2 Announce Type: replace-cross Abstract: Accurate and reliable forecasting of epidemic incidences is critical for public health preparedness, yet it remains a challenging task due to

Deep Learning-Based Characterization of Detonation-Cell Size Distributions in Soot-Foil Records

model-releasesarxiv-cs-cv

arXiv:2607.03764v1 Announce Type: cross Abstract: The geometric size and regularity of detonation cells are key physical parameters for characterizing detonation waves. Traditional manual measurement

Deep Learning for Dynamic Programming with Recursive Utility

arXiv:2607.04278v1 Announce Type: cross Abstract: We propose the first deep learning algorithm, the Certainty Equivalent Learning (CEL) algorithm, for solving high-dimensional discrete-time dynamic pr

safetyarxiv-cs-lg

Deep Learning for Semen Analysis in Male Infertility: Computer Vision, Multimodal Fusion, and Clinical Translation

arXiv:2607.05311v1 Announce Type: new Abstract: Male infertility contributes substantially to the global infertility burden, and sperm analysis remains central to diagnosis, treatment planning, and as

applicationsarxiv-cs-cv

Deep Learning Network-Temporal Models For Traffic Prediction

arXiv:2603.11475v2 Announce Type: replace Abstract: Accurate prediction of multivariate time series is essential for emerging network intelligent control, observability, and management functions. Exis

Defending from GeoLocalization through Adversarial Road Trips

arXiv:2607.03277v1 Announce Type: new Abstract: Retrieval-based image geolocalization has emerged as a powerful technique for determining the location of a query image by matching it against a large,

safetyarxiv-cs-cv

Deform360: A Massive Multi-view Visuotactile Dataset for Deformable World Models

model-releasesarxiv-cs-cv

arXiv:2607.05390v1 Announce Type: cross Abstract: Predicting object dynamics (i.e., world modeling) is a fundamental challenge for robotic manipulation, and modeling deformable objects presents a part