Imagen de Portada

DeepDiveAI: Identifying AI Related Documents in Large Scale Literature Data

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Xiaochen, Zhou, Xingzhou, Liang, Hui, Zou, Yi, Lu, Jingjing, Qu
Formato:	Preprint
Publicado:	2024
Materias:	Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Global Dataset Mapping the AI Innovation from Academic Research to Industrial Patents
por: Gong, Haixing, et al.
Publicado: (2025)

Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on Hugging Face
por: Yang, Xinyu, et al.
Publicado: (2024)

From Principles to Practice: A Deep Dive into AI Ethics and Regulations
por: Sun, Nan, et al.
Publicado: (2024)

Is Agentic AI Ready for Real-World Hardware Engineering? A Deep Dive with Phoenix-bench
por: Zou, Qingyun, et al.
Publicado: (2026)

Breaking Android with AI: A Deep Dive into LLM-Powered Exploitation
por: Perera, Wanni Vidulige Ishan, et al.
Publicado: (2025)

A Deep Dive into Scaling RL for Code Generation with Synthetic Data and Curricula
por: Sancaktar, Cansu, et al.
Publicado: (2026)

AI for All: Identifying AI incidents Related to Diversity and Inclusion
por: Shams, Rifat Ara, et al.
Publicado: (2024)

Exploring the Vulnerabilities of Federated Learning: A Deep Dive into Gradient Inversion Attacks
por: Guo, Pengxin, et al.
Publicado: (2025)

Bridging AI and Science: Implications from a Large-Scale Literature Analysis of AI4Science
por: Xie, Yutong, et al.
Publicado: (2024)

MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation
por: Zhang, Haoxuan, et al.
Publicado: (2026)

AIDABench: AI Data Analytics Benchmark
por: Yang, Yibo, et al.
Publicado: (2026)

DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models
por: Xiong, Luolin, et al.
Publicado: (2025)

Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness
por: Guo, Kai, et al.
Publicado: (2024)

AI Learning Algorithms: Deep Learning, Hybrid Models, and Large-Scale Model Integration
por: Golilarz, Noorbakhsh Amiri, et al.
Publicado: (2024)

Fragile Preferences: A Deep Dive Into Order Effects in Large Language Models
por: Yin, Haonan, et al.
Publicado: (2025)

Assessing AI Detectors in Identifying AI-Generated Code: Implications for Education
por: Pan, Wei Hung, et al.
Publicado: (2024)

AdaQE-CG: Adaptive Query Expansion for Web-Scale Generative AI Model and Data Card Generation
por: Zhang, Haoxuan, et al.
Publicado: (2026)

What is Google Health AI? A Deep Dive into the Future of Digital Medicine
por: www.rasitdinc.com
Publicado: (2024)

MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark
por: Fan, Shiqing, et al.
Publicado: (2025)

A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Models
por: Ning, Liangbo, et al.
Publicado: (2025)

Scaling Laws for Educational AI Agents
por: Wu, Mengsong, et al.
Publicado: (2026)

Identifying and Mitigating the Security Risks of Generative AI
por: Barrett, Clark, et al.
Publicado: (2023)

Reflection on Data Storytelling Tools in the Generative AI Era from the Human-AI Collaboration Perspective
por: Li, Haotian, et al.
Publicado: (2025)

Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling
por: Li, Haotian, et al.
Publicado: (2023)

Data-Free Model-Related Attacks: Unleashing the Potential of Generative AI
por: Ye, Dayong, et al.
Publicado: (2025)

The Novelty Bottleneck: A Framework for Understanding Human Effort Scaling in AI-Assisted Work
por: Liang, Jacky
Publicado: (2026)

STaR: Sensitive Trajectory Regulation for Unlearning in Large Reasoning Models
por: Zhou, Jingjing, et al.
Publicado: (2026)

Flowr -- Scaling Up Retail Supply Chain Operations Through Agentic AI in Large Scale Supermarket Chains
por: Bandara, Eranga, et al.
Publicado: (2026)

DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
por: Xin, Huajian, et al.
Publicado: (2024)

Data-Driven Analysis of AI in Medical Device Software in China: Trends of Deep Learning and Traditional AI Based on Regulatory Data
por: Han, Yu, et al.
Publicado: (2024)

Paper2Data: Large-Scale LLM Extraction and Metadata Structuring of Global Urban Data from Scientific Literature
por: You, Runwen, et al.
Publicado: (2026)

Textual Equilibrium Propagation for Deep Compound AI Systems
por: Chen, Minghui, et al.
Publicado: (2026)

Continued AI Scaling Requires Repeated Efficiency Doublings
por: Lu, Chien-Ping
Publicado: (2026)

StrucText-Eval: Evaluating Large Language Model's Reasoning Ability in Structure-Rich Text
por: Gu, Zhouhong, et al.
Publicado: (2024)

Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models
por: Wei, Tianwen, et al.
Publicado: (2024)

Identifying Trustworthiness Challenges in Deep Learning Models for Continental-Scale Water Quality Prediction
por: Xia, Xiaobo, et al.
Publicado: (2025)

Does AI Respect Medical Ethics Principles? A Deep Dive into Digital Health
por: www.rasitdinc.com
Publicado: (2021)

Identifying, Evaluating, and Mitigating Risks of AI Thought Partnerships
por: Oktar, Kerem, et al.
Publicado: (2025)

Responsible AI: Portraits with Intelligent Bibliometrics
por: Zhang, Yi, et al.
Publicado: (2024)

Jailbreak-as-a-Service++: Unveiling Distributed AI-Driven Malicious Information Campaigns Powered by LLM Crowdsourcing
por: Yan, Yu, et al.
Publicado: (2025)