Search: “framework”

When Bots Join the Team: Bot Adoption and the Institutional Fabric of Open-Source Software Projects

arXiv:2607.13679v1 Announce Type: new Abstract: AI agents are joining human teams, raising a basic question: when an automated agent becomes a regular participant, does group organization strengthen o

16 Jul 2026

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When T2I Synthetic Data Backfires: Amplified Privacy Risks in Real-Synthetic Mix Training

DGX agent

arXiv:2607.13541v1 Announce Type: cross Abstract: To overcome data scarcity and privacy constraints in data collection, it has become standard practice across academia and industry to augment real tra

researcharxiv-cs-lg

16 Jul 2026

Where Should RL Post-Training Compute Go? Model Size, Search, Learning, and Feedback

arXiv:2607.13389v1 Announce Type: new Abstract: Reinforcement Learning (RL) post-training is increasingly used to adapt foundation models for reasoning, planning, and feedback-driven robot-learning pi

16 Jul 2026

WNOJ-LIO: A White-Noise-on-Jerk Motion-Prior EKF for High-Dynamic LiDAR-IMU Fusion

arXiv:2607.13405v1 Announce Type: new Abstract: LiDAR-inertial odometry (LIO) is a key component of autonomous navigation, but high-dynamic driving exposes two coupled challenges: intra-scan motion di

agentsarxiv-cs-ro

16 Jul 2026

A Comparative Analysis of Institutional and Course Generative AI Policies within Higher Education: Implications for Instruction in Computing Education

arXiv:2607.12296v1 Announce Type: cross Abstract: With the increased use of generative AI (GenAI) applications such as ChatGPT, higher education institutions (HEIs) have released a range of guidelines

A hybrid analytical-PINN model for subsurface simulation of geothermal heat exchangers in heterogeneous underground

arXiv:2607.12271v1 Announce Type: new Abstract: In this paper, a parametric physics-informed neural network for solving the heterogeneous soil thermal problem with borehole heat exchangers (BHEs) as s

researcharxiv-cs-lg

A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs

arXiv:2602.19938v2 Announce Type: replace Abstract: Sparse Mixture-of-Experts (SMoE) architectures are increasingly used to scale large language models efficiently, delivering strong accuracy under fi

researcharxiv-cs-lg

ABot-3DWorld 0: A Universal World Model to Explore Any 3D Space

arXiv:2607.11673v2 Announce Type: replace Abstract: We present ABot-3DWorld 0, a universal multimodal 3D world model that turns text, image, and video inputs into high-fidelity, explorable 3D worlds.

researcharxiv-cs-cv

AdaPCLA: Adaptive Prior-Calibrated Logit Adjustment for Long-Tailed Longitudinal EHR Generation

arXiv:2607.12645v1 Announce Type: new Abstract: Generative modeling of longitudinal Electronic Health Records is increasingly important for privacy-preserving research, yet standard autoregressive mod

applicationsarxiv-cs-lg

Adaptive Cross-Modal Fusion with Sparse Attention for Pedestrian Crossing Intention Prediction

arXiv:2607.12293v1 Announce Type: new Abstract: Predicting pedestrian crossing intention is a safety-critical task for autonomous driving, yet existing approaches often rely on single-modal inputs or

Adaptive Testing for LLM Evaluation: A Psychometric Alternative to Static Benchmarks

arXiv:2511.04689v3 Announce Type: replace-cross Abstract: Evaluating large language models (LLMs) typically requires thousands of benchmark items, making the process expensive, slow, and increasingly

Adversarial Attacks on Online Handwriting using Salience-based Temporal Editing

arXiv:2607.12500v1 Announce Type: cross Abstract: Deep learning models for online handwriting recognition have been shown effective and are increasingly deployed in practical applications. However, th

researcharxiv-cs-cv

AgentCheck: A Reproduce-Intervene-Mitigate Workbench for LLM Agents over MCP

arXiv:2607.11098v2 Announce Type: replace-cross Abstract: Tool-using LLM agents are mostly evaluated assuming all tools work. When a tool times out, returns a week-stale value, or has its description

Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing

arXiv:2607.12619v1 Announce Type: new Abstract: The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goa

Tutorials

Anatomy-Privileged Distillation with Token Routing for MRI-Based Prediction of Perineural Invasion

arXiv:2607.11987v1 Announce Type: new Abstract: Perineural invasion (PNI) is associated with poor postoperative outcomes in intrahepatic cholangiocarcinoma, but it is confirmed by surgical pathology.

tutorialsarxiv-cs-cv

Auditable Context-Aware HFMD Forecasting with Structured LLM Agents

arXiv:2511.23276v2 Announce Type: replace Abstract: Effective HFMD surveillance requires forecasts capturing both time-series patterns and contextual drivers such as school calendars, weather, and pol

Auditing Data Leakage in Whole-Slide Image Multimodal Benchmarks

arXiv:2607.12278v1 Announce Type: new Abstract: Recent vision-language models (VLMs) for computational pathology report striking zero-shot performance on whole-slide image (WSI) visual question answer

AVSCap: Orchestrating Audio-Visual Synergy for Omni-modal Video Captioning

arXiv:2607.12820v1 Announce Type: new Abstract: Omni-modal video captioning is not merely combining visual captioning with audio transcription: a useful caption must describe how visual actions, speec

Beyond Binary Detection: A Multi-Dimensional Taxonomy of Cancer Misinformation on Reddit

arXiv:2607.12383v1 Announce Type: new Abstract: Cancer-related discussions on social media provide an important space for information exchange and peer support, but also facilitate the spread of misin

researcharxiv-cs-cl

Beyond Perfect Priors: Adaptive Gaussian Graph for 4D Driving Reconstruction in the Wild

arXiv:2607.12214v1 Announce Type: new Abstract: Reconstructing 4D driving scenes in the wild (e.g., internet and AI-generated videos) is critical for diverse autonomous driving simulation. While recen

Breaking Deja Vu: Independent Auditing of Visual Place Recognition through Vision-Language Reasoning

arXiv:2607.12818v1 Announce Type: new Abstract: Visual place recognition (VPR) is a key enabler of accurate localization and long-term autonomous navigation in robotics applications, such as loop clos

Bulkhead: Automated Semantic Detection and Remediation of Container Escape Vulnerabilities

arXiv:2607.12723v1 Announce Type: cross Abstract: Filesystem isolation in container ecosystems is often weakened by cross-boundary path misresolution, causing path traversal (PaTra) vulnerabilities. T

CANDI: Contextual Alignment for Niche Domains Question Answering

arXiv:2607.11891v1 Announce Type: cross Abstract: The deployment of large language models (LLMs) in specialized domains like medical diagnostics and financial advisory necessitates evaluating capabili

CARE-LoRA: Compressed Activation REconstruction for Memory-Efficient LoRA

arXiv:2607.11940v1 Announce Type: cross Abstract: As the scale of large pre-trained models continues to grow, fine-tuning them under limited memory budgets has become increasingly challenging. Low-Ran

CASHEW: Stabilizing Multimodal Reasoning via Iterative Trajectory Aggregation

arXiv:2601.08010v3 Announce Type: replace Abstract: Vision-language models achieve strong performance across a wide range of multimodal understanding and reasoning tasks, yet their multi-step reasonin

safetyarxiv-cs-cv

CGRL: Concept-Guided Pruning and Representation Learning for Whole-Slide Image Classification

arXiv:2607.12556v1 Announce Type: new Abstract: Weakly supervised whole-slide image (WSI) classification is widely used in computational pathology because slide-level labels are easier to obtain than

safetyarxiv-cs-cv

ChartGenEval: Corruption-Tested Multi-Dimensional Feedback for Rhythm-Game Chart Generation

arXiv:2607.12857v1 Announce Type: cross Abstract: A generated rhythm-game chart need not reproduce one official note sequence: many note choices can fit the same song and difficulty. Reference-note ag

researcharxiv-cs-ai

ChunkFlow: Towards Continuity-Consistent Chunked Policy Learning

arXiv:2607.12992v1 Announce Type: new Abstract: Vision-language action (VLA) models increasingly adopt chunked action heads to satisfy real-time constraints; however, this introduces boundary jitter:

safetyarxiv-cs-ro

Code-MUE: Measuring Code LLMs' Uncertainty through Execution-based Semantic Interaction Graphs

arXiv:2607.12273v1 Announce Type: cross Abstract: As Code Large Language Models (LLMs) become central to modern software engineering, their inherent stochasticity poses significant real-world risks, w

safetyarxiv-cs-ai

Color Pass-Through via Camera-Display Coupling

arXiv:2607.12746v1 Announce Type: new Abstract: When a real-world scene is captured by a smartphone camera and viewed on its screen, the displayed image often differs noticeably from the original scen

applicationsarxiv-cs-cv

Continual Learning with Elastic Regularization and Synthetic Replay for Federated MLLM Fine-Tuning

arXiv:2607.12112v1 Announce Type: cross Abstract: Federated fine-tuning of Multimodal Large Language Models (MLLMs) across distributed networks enables privacy-sensitive adaptation to evolving data st

Continuous Policy and Value Iteration for Stochastic Control Problems and Its Convergence

arXiv:2506.08121v2 Announce Type: replace-cross Abstract: We introduce a continuous policy-value iteration algorithm where the approximations of the value function of a stochastic control problem and

Contract-Grounded Behavior Tree Synthesis via Coding Agents

arXiv:2607.12220v1 Announce Type: new Abstract: Synthesizing deployable robot behavior trees (BTs) from natural language (NL) requires grounding to ensure every generated BT references only skills a r

agentsarxiv-cs-ro

Contrastive-Augmented Flow Matching for Style-Content Disentanglement

arXiv:2607.12404v1 Announce Type: new Abstract: Learning representations that separate content and style is crucial for controllable generation and compositional generalization. However, diffusion and

applicationsarxiv-cs-cv

Critic Experience Bank: Self-Evolving Step-Level Confidence Estimation for LLM Agents

arXiv:2607.12397v1 Announce Type: new Abstract: LLM agents act in external environments where each action changes the state that later decisions condition on, and where a single wrong step can waste i

DA-Nav: Direction-Aware City-Scale Vision-Language Navigation

arXiv:2607.11638v2 Announce Type: replace Abstract: City-scale outdoor navigation is currently hindered by the heavy reliance on dense maps or costly navigation supervision. In this work, we introduce

applicationsarxiv-cs-ro

Decentralized Gradient Descent: Bottleneck Regimes and Budget Complexity

arXiv:2607.12172v1 Announce Type: cross Abstract: Decentralized gradient descent (DGD) is widely used for solving distributed optimization problems over networks of agents. While its convergence prope

researcharxiv-cs-lg

Decouple and Reason: Anatomically Guided Two-Stage Voxel-Level Grounding of Free-Text Findings in 3D Chest CT

arXiv:2607.12602v1 Announce Type: new Abstract: Automatic voxel-level grounding of free-text findings in 3D chest Computed Tomography (CT) is critical for clinical interpretability. However, this task

Deep Learning-based Surrogate Modelling of the LOD Method for Multiscale Problems

arXiv:2607.12570v1 Announce Type: cross Abstract: Multiscale problems are notoriously difficult to tackle using traditional numerical methods, as accurately resolving fine-scale features often require

researcharxiv-cs-ai

Deep4ge: DNN Training Trajectories for Fault Detection and Diagnosis

model-releasesarxiv-cs-lg

arXiv:2607.12868v1 Announce Type: cross Abstract: Deep learning systems often fail due to subtle implementation faults that alter training behavior. Recent work has studied how to detect and diagnose

DeGuNet: Depth-Guided Ultra-Compact Backbones for Efficient LiDAR-Camera 3D Detection

arXiv:2607.12419v1 Announce Type: new Abstract: In autonomous driving perception, the fusion of LiDAR and camera modalities has become the dominant paradigm for 3D object detection. However, current m

Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences

arXiv:2607.12466v1 Announce Type: new Abstract: Aligning robot policies with human preferences is essential for deployment to diverse end users. In per-user alignment approach, preference feedback is

safetyarxiv-cs-ro

Diffusion Denoiser-Aided Gyrocompassing

arXiv:2507.21245v2 Announce Type: replace-cross Abstract: An accurate initial heading angle is essential for efficient and safe navigation across diverse domains. Unlike magnetometers, gyroscopes can

agentsarxiv-cs-lg

Directional Constraints for Efficient Exploration in Safe Reinforcement Learning

arXiv:2607.12784v1 Announce Type: cross Abstract: Reinforcement Learning has revolutionized the landscape of robotic research, allowing robust learning of complex robotic skills in simulation. However

Tutorials

Diversity-Enriched Option-Critic

arXiv:2011.02565v2 Announce Type: replace-cross Abstract: Temporal abstraction allows reinforcement learning agents to represent knowledge and develop strategies over different temporal scales. The op

tutorialsarxiv-cs-ai

Do AI Agents Know When a Task Is Simple? Toward Complexity-Aware Reasoning and Execution

arXiv:2607.13034v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly automate multi-step engineering and informatics workflows, yet they rarely ask how much effort a task act

Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?

arXiv:2607.12787v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) have significantly improved the performance of multimodal emotion recognition (MER) and enab

Do We Really Need Transformers for Global Spatial Information Extraction in Traffic Forecasting?

arXiv:2607.12462v1 Announce Type: new Abstract: Existing traffic forecasting models commonly focus on extracting spatial dependencies, particularly global spatial information, which characterizes the

researcharxiv-cs-ai