·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Integrating High-Level Requirements to Low-Level Tests with Machine-Readable V&V Specifications12m◆Lifelong Multi-Subsystem Pickup and Delivery with Buffer-Limited Handover Stations12m◆MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference12m◆Mobile Network Control with a World Model12m◆DA-Fusion: Deformable Attention-Based RGB-D Fusion Transformer for Unseen Object Instance Segmentation12m◆Seg2Grasp: A Robust Modular Suction Grasping in Bin Picking12m◆Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning12m◆Time-Frequency Consistency Learning for Robust Speech Deepfake Detection12m◆Autonomous Discovery of Wireless Communications Algorithms12m◆FIFA World Cup 2026 as a Contamination-Free Benchmark for LLM Forecasting Agents: Four Models, a Bookmaker, and 104 Matches12m◆Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence12m◆Persona-as-Configuration: Generative Stakeholder Reporting for Agricultural Floods12m◆CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging12m◆ETAS: An Effect-Typed Language for Agent Systems12m◆BrainNext: A General-Purpose Self-Supervised Foundation Model for Brain MRI Analysis12m◆Feature Attribution-Based Explainability Analysis of Deep Learning Models in Predictive Process Monitoring12m◆Reasoning as a Double-Edged Sword: Architecture and Cross-Stage Robustness in Vision-Language-Action Models12m◆Medical Imaging Fusing Vision Transformer: Laryngeal Cancer Screening with Explanation12m◆ReViV: Reconstructing the Viewer and the View in 4D from Monocular Egocentric Video12m◆Vis2Reg: Visibility-Aware Landmark-Free Geometric 3D--2D Registration for Liver Laparoscopy12m◆Integrating High-Level Requirements to Low-Level Tests with Machine-Readable V&V Specifications12m◆Lifelong Multi-Subsystem Pickup and Delivery with Buffer-Limited Handover Stations12m◆MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference12m◆Mobile Network Control with a World Model12m◆DA-Fusion: Deformable Attention-Based RGB-D Fusion Transformer for Unseen Object Instance Segmentation12m◆Seg2Grasp: A Robust Modular Suction Grasping in Bin Picking12m◆Generalize and Guide: Decomposing Rewards for Few-Shot Inverse Reinforcement Learning12m◆Time-Frequency Consistency Learning for Robust Speech Deepfake Detection12m◆Autonomous Discovery of Wireless Communications Algorithms12m◆FIFA World Cup 2026 as a Contamination-Free Benchmark for LLM Forecasting Agents: Four Models, a Bookmaker, and 104 Matches12m◆Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence12m◆Persona-as-Configuration: Generative Stakeholder Reporting for Agricultural Floods12m◆CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging12m◆ETAS: An Effect-Typed Language for Agent Systems12m◆BrainNext: A General-Purpose Self-Supervised Foundation Model for Brain MRI Analysis12m◆Feature Attribution-Based Explainability Analysis of Deep Learning Models in Predictive Process Monitoring12m◆Reasoning as a Double-Edged Sword: Architecture and Cross-Stage Robustness in Vision-Language-Action Models12m◆Medical Imaging Fusing Vision Transformer: Laryngeal Cancer Screening with Explanation12m◆ReViV: Reconstructing the Viewer and the View in 4D from Monocular Egocentric Video12m◆Vis2Reg: Visibility-Aware Landmark-Free Geometric 3D--2D Registration for Liver Laparoscopy12m◆
News/Customized Generative AI Agent for Transportation Engineering Practice: A Development and Continued Pre-training Guideline
arxiv
PublishedJune 30, 2026 at 4:00 AM

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

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

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 reasoning, summarization, and question-answering tasks. However, the effectiveness of general-purpose L

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivIntegrating High-Level Requirements to Low-Level Tests with Machine-Readable V&V Specifications12marxivLifelong Multi-Subsystem Pickup and Delivery with Buffer-Limited Handover Stations12marxivMXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference12marxivMobile Network Control with a World Model12m
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews