System: You are an **advanced AI assistant** capable of detailed, multi-step problem solving. Break down tasks into clear, logical steps. Explain each step thoroughly and provide a final answer. If you need additional information, use the following format for search queries IMPORTANT:

```search
{
  "queries": [
    "first search query",
    "second search query",
    "third search query",
    "etc"
  ]
}```

User: Query: give me the list with urls of the latest most important research papers in AI in 2024, with small summaries for them

Iteration: 1

Previous Attempts:


Relevant Info:
Timestamp: 2024-09-22 08:34:56 || [{'title': '10 Breakthrough AI Research Papers to Read in 2024 | Analytics Insight', 'summary': '10 Breakthrough AI Research Papers to Read in 2024 | Analytics Insight...', 'url': 'https://www.analyticsinsight.net/artificial-intelligence/10-breakthrough-ai-research-papers-to-read-in-2024', 'extracted_content': ''}, {'title': '[2405.19522] Artificial Intelligence Index Report 2024 | arXiv.org', 'summary': '[2405.19522] Artificial Intelligence Index Report 2024 | arXiv.org...', 'url': 'https://arxiv.org/abs/2405.19522', 'extracted_content': "Computer Science > Artificial Intelligence Title: Artificial Intelligence Index Report 2024 Submission history Access Paper: View PDF Other Formats References & Citations NASA ADS Google Scholar Semantic Scholar BibTeX formatted citation Bookmark Bibliographic and Citation Tools Code, Data and Media Associated with this Article Demos Recommenders and Search Tools Author Venue Institution Topic arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . "}, {'title': 'What are the most influential current AI Papers? | by NLLG | Medium', 'summary': 'What are the most influential current AI Papers? | by NLLG | Medium...', 'url': 'https://medium.com/@nllg/what-are-the-most-influential-current-ai-papers-affb3cdc5c6a', 'extracted_content': 'What are the most influential current AI Papers? NLLG Follow 6 Listen Share NLLG Quarterly arXiv Report 06/23 The advent of ChatGPT in late 2022 has marked a paradigm in AI research. Since then, not only public attention on AI technologies has spiked. Also, research output has flourished. The sheer amount of new research published each week and month, against the background of already exponential growth of science, may overwhelm not only newcomers and outsiders of AI. To alleviate this problem, here, we present the top influential papers (in terms of citations) between January and June 2023 from the AI subfields of Machine Learning (ML) and Natural Language Processing (NLP), sourced from arXiv . We focus on arXiv , because it is a popular open-access archive of scholarly articles that has operated for the last decades. In an age of rapid developments, conferences and journals are often too slow and lagging behind recent developments. Conferences may also (increasingly) suffer from low reviewing quality, with junior and non-expert reviewers abounding. In contrast, arXiv may host the latest research immediately and by focusing on citations we forgo the problematic review process. To facilitate the selection of the top papers, we adopt a straightforward approach of choosing papers from arXiv’s database for the initial half of the year 2023. Subsequently, we sort these papers based on their normalized citation counts (which we call z-score; see below). arXiv categorizes its content into various subject areas or disciplines to help researchers and readers find relevant papers easily. Each of these main categories is further divided into subcategories to narrow down the topics within those domains. For example, within the “Computer Science” (cs) category, one can find subcategories such as Artificial Intelligence (cs.AI), Machine Learning (cs.LG), Natural Language Processing (cs.CL), Computer Vision (cs.CV), etc. [ link to category taxonomy ] We collect all papers from 01'}]
Timestamp: 2024-09-22 08:35:33 || [{'title': 'The 27 Most Influential AI Research Papers (2024) - Medium', 'summary': 'The 27 Most Influential AI Research Papers (2024) - Medium...', 'url': 'https://blog.cschmidl.com/the-27-most-influential-ai-research-papers-2024-b30e98817fcd', 'extracted_content': 'Member-only story The 27 Most Influential AI Research Papers (2024) According to Ilya Sutskever: “If you really learn all of these, you’ll know 90% of what matters today” Christoph Schmidl Follow 1 Listen Share Introduction I recently came across several posts on LinkedIn and Reddit that mentioned 27 papers given to John Carmack by Ilya Sutskever to help him understand most of the current Artificial Intelligence (AI) techniques. John Carmack is a game developer (Doom) and rocket engineer now shifting toward AI. One common quote that often pops up in this context is the following: “S o I asked Ilya Sutskever, OpenAI’s chief scientist, for a reading list. He gave me a list of like 40 research papers and said, ‘If you really learn all of these, you’ll know 90% of what matters today.’ And I did. I plowed through all those things and it all started sorting out in my head.” — John Carmack ( Source ) Although the quote mentions 40 research papers, I only found 27 of them… and not even all of them are actual research papers :) Who is Ilya Sutskever , and why should you care?'}, {'title': '10 Breakthrough AI Research Papers to Read in 2024 - Analytics Insight', 'summary': '10 Breakthrough AI Research Papers to Read in 2024 - Analytics Insight...', 'url': 'https://www.analyticsinsight.net/artificial-intelligence/10-breakthrough-ai-research-papers-to-read-in-2024', 'extracted_content': ''}, {'title': '[2405.19522] Artificial Intelligence Index Report 2024 - arXiv.org', 'summary': '[2405.19522] Artificial Intelligence Index Report 2024 - arXiv.org...', 'url': 'https://arxiv.org/abs/2405.19522', 'extracted_content': "Computer Science > Artificial Intelligence Title: Artificial Intelligence Index Report 2024 Submission history Access Paper: View PDF Other Formats References & Citations NASA ADS Google Scholar Semantic Scholar BibTeX formatted citation Bookmark Bibliographic and Citation Tools Code, Data and Media Associated with this Article Demos Recommenders and Search Tools Author Venue Institution Topic arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . "}]
Timestamp: 2024-09-22 08:36:09 || [{'title': 'Recent articles and discoveries in Artificial Intelligence - Springer', 'summary': 'Recent articles and discoveries in Artificial Intelligence - Springer...', 'url': 'https://link.springer.com/subject/artificial-intelligence', 'extracted_content': 'Rapid stability assessment of barrier dams based on the extreme gradient boosting model Haiqing Yang Hao Li Xinchang Liu'}, {'title': 'Journal of Artificial Intelligence Research', 'summary': 'Journal of Artificial Intelligence Research...', 'url': 'https://www.jair.org/', 'extracted_content': 'Main Navigation Main Content Sidebar Register Login  Current Archives About About the Journal JAIR Transparent Publishing Submissions Masthead News FAQ Contact About the Journal JAIR Transparent Publishing Submissions Masthead News FAQ Contact Special Tracks Surveys IJCAI-JAIR Awards Conference Award Track AI and Society Constraint Programming and Machine Learning Multi-Agent Path Finding Fairness and Bias in AI Hybrid Human-Artificial Intelligence AI and COVID-19 Deep Learning, Knowledge Representation and Reasoning Cross-Language Algorithms and Applications Description Logics Nonmonotonic Reasoning 4th International Planning Competition 3rd International Planning Competition Surveys IJCAI-JAIR Awards Conference Award Track AI and Society Constraint Programming and Machine Learning Multi-Agent Path Finding Fairness and Bias in AI Hybrid Human-Artificial Intelligence AI and COVID-19 Deep Learning, Knowledge Representation and Reasoning Cross-Language Algorithms and Applications Description Logics Nonmonotonic Reasoning 4th International Planning Competition 3rd International Planning Competition The Journal of Artificial Intelligence Research (JAIR) is dedicated to the rapid dissemination of important research results to the global artificial intelligence (AI) community. The journal’s scope encompasses all areas of AI, including agents and multi-agent systems, automated reasoning, constraint processing and search, knowledge representation, machine learning, natural language, planning and scheduling, robotics and vision, and uncertainty in AI. Current Issue Vol. 81 (2024) Published: 2024-09-11 Articles Opening the Analogical Portal to Explainability: Can Analogies Help Laypeople in AI-assisted Decision Making? 117-162 Separating and Collapsing Electoral Control Types 71-116 The State of Computer Vision Research in Africa 43-69 Understanding What Affects the Generalization Gap in Visual Reinforcement Learning: Theory and Empirical Evidence 1-42 news 2024 IJCAI-JAIR Pr'}, {'title': 'AIJ | Artificial Intelligence | Journal - ScienceDirect', 'summary': 'AIJ | Artificial Intelligence | Journal - ScienceDirect...', 'url': 'https://www.sciencedirect.com/journal/artificial-intelligence', 'extracted_content': 'Your Browser is out of date. Update your browser to view ScienceDirect. View recommended browsers . Request details: About ScienceDirect Shopping cart Contact and support Terms and conditions Privacy policy Cookies are used by this site. By continuing you agree to the use of cookies . Copyright © 2024 Elsevier B.V., its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the Creative Commons licensing terms apply.'}]
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