NLLG Quarterly arXiv Report 09/23: What are the most influential current AI Papers?
Artificial Intelligence (AI) has witnessed rapid growth, especially in the subfields Natural Language Processing (NLP), Machine Learning (ML) and Computer Vision (CV). Keeping pace with this rapid progress poses a considerable challenge for researchers and professionals in the field. In this arXiv r...
Gespeichert in:
Hauptverfasser: | , , , , , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | |
container_volume | |
creator | Zhang, Ran Kostikova, Aida Leiter, Christoph Belouadi, Jonas Larionov, Daniil Chen, Yanran Fresen, Vivian Eger, Steffen |
description | Artificial Intelligence (AI) has witnessed rapid growth, especially in the
subfields Natural Language Processing (NLP), Machine Learning (ML) and Computer
Vision (CV). Keeping pace with this rapid progress poses a considerable
challenge for researchers and professionals in the field. In this arXiv report,
the second of its kind, which covers the period from January to September 2023,
we aim to provide insights and analysis that help navigate these dynamic areas
of AI. We accomplish this by 1) identifying the top-40 most cited papers from
arXiv in the given period, comparing the current top-40 papers to the previous
report, which covered the period January to June; 2) analyzing dataset
characteristics and keyword popularity; 3) examining the global sectoral
distribution of institutions to reveal differences in engagement across
geographical areas. Our findings highlight the continued dominance of NLP:
while only 16% of all submitted papers have NLP as primary category (more than
25% have CV and ML as primary category), 50% of the most cited papers have NLP
as primary category, 90% of which target LLMs. Additionally, we show that i)
the US dominates among both top-40 and top-9k papers, followed by China; ii)
Europe clearly lags behind and is hardly represented in the top-40 most cited
papers; iii) US industry is largely overrepresented in the top-40 most
influential papers. |
doi_str_mv | 10.48550/arxiv.2312.05688 |
format | Article |
fullrecord | <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2312_05688</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2312_05688</sourcerecordid><originalsourceid>FETCH-LOGICAL-a678-3d4638175a3346e1b07dabe9b4368b8c97f3e5143d5acbd0883754a4945b88043</originalsourceid><addsrcrecordid>eNotz8FKw0AUBdDZuJDqB7jy_UDSSd5M8uJGStFaCGprQXfhTTKhA2kbJpNi_95aXd0LFy4cIe4SGSvSWk7Zf7tjnGKSxlJnRNfi47UsF7Aa2QfruxOw_3JHWNv-4APIYpriA3xuOZwHC2FrYXcYArh92412Hxx3UI_enyvMlvDOvfXD4424arkb7O1_TsTm-Wkzf4nKt8VyPisjznKKsFEZUpJrRlSZTYzMGza2MAozMlQXeYtWJwobzbVpJBHmWrEqlDZEUuFE3P_dXlRV792O_an61VUXHf4AsY5IBw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>NLLG Quarterly arXiv Report 09/23: What are the most influential current AI Papers?</title><source>arXiv.org</source><creator>Zhang, Ran ; Kostikova, Aida ; Leiter, Christoph ; Belouadi, Jonas ; Larionov, Daniil ; Chen, Yanran ; Fresen, Vivian ; Eger, Steffen</creator><creatorcontrib>Zhang, Ran ; Kostikova, Aida ; Leiter, Christoph ; Belouadi, Jonas ; Larionov, Daniil ; Chen, Yanran ; Fresen, Vivian ; Eger, Steffen</creatorcontrib><description>Artificial Intelligence (AI) has witnessed rapid growth, especially in the
subfields Natural Language Processing (NLP), Machine Learning (ML) and Computer
Vision (CV). Keeping pace with this rapid progress poses a considerable
challenge for researchers and professionals in the field. In this arXiv report,
the second of its kind, which covers the period from January to September 2023,
we aim to provide insights and analysis that help navigate these dynamic areas
of AI. We accomplish this by 1) identifying the top-40 most cited papers from
arXiv in the given period, comparing the current top-40 papers to the previous
report, which covered the period January to June; 2) analyzing dataset
characteristics and keyword popularity; 3) examining the global sectoral
distribution of institutions to reveal differences in engagement across
geographical areas. Our findings highlight the continued dominance of NLP:
while only 16% of all submitted papers have NLP as primary category (more than
25% have CV and ML as primary category), 50% of the most cited papers have NLP
as primary category, 90% of which target LLMs. Additionally, we show that i)
the US dominates among both top-40 and top-9k papers, followed by China; ii)
Europe clearly lags behind and is hardly represented in the top-40 most cited
papers; iii) US industry is largely overrepresented in the top-40 most
influential papers.</description><identifier>DOI: 10.48550/arxiv.2312.05688</identifier><language>eng</language><subject>Computer Science - Artificial Intelligence ; Computer Science - Computation and Language ; Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Computers and Society ; Computer Science - Digital Libraries ; Computer Science - Learning</subject><creationdate>2023-12</creationdate><rights>http://creativecommons.org/licenses/by-sa/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2312.05688$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2312.05688$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Ran</creatorcontrib><creatorcontrib>Kostikova, Aida</creatorcontrib><creatorcontrib>Leiter, Christoph</creatorcontrib><creatorcontrib>Belouadi, Jonas</creatorcontrib><creatorcontrib>Larionov, Daniil</creatorcontrib><creatorcontrib>Chen, Yanran</creatorcontrib><creatorcontrib>Fresen, Vivian</creatorcontrib><creatorcontrib>Eger, Steffen</creatorcontrib><title>NLLG Quarterly arXiv Report 09/23: What are the most influential current AI Papers?</title><description>Artificial Intelligence (AI) has witnessed rapid growth, especially in the
subfields Natural Language Processing (NLP), Machine Learning (ML) and Computer
Vision (CV). Keeping pace with this rapid progress poses a considerable
challenge for researchers and professionals in the field. In this arXiv report,
the second of its kind, which covers the period from January to September 2023,
we aim to provide insights and analysis that help navigate these dynamic areas
of AI. We accomplish this by 1) identifying the top-40 most cited papers from
arXiv in the given period, comparing the current top-40 papers to the previous
report, which covered the period January to June; 2) analyzing dataset
characteristics and keyword popularity; 3) examining the global sectoral
distribution of institutions to reveal differences in engagement across
geographical areas. Our findings highlight the continued dominance of NLP:
while only 16% of all submitted papers have NLP as primary category (more than
25% have CV and ML as primary category), 50% of the most cited papers have NLP
as primary category, 90% of which target LLMs. Additionally, we show that i)
the US dominates among both top-40 and top-9k papers, followed by China; ii)
Europe clearly lags behind and is hardly represented in the top-40 most cited
papers; iii) US industry is largely overrepresented in the top-40 most
influential papers.</description><subject>Computer Science - Artificial Intelligence</subject><subject>Computer Science - Computation and Language</subject><subject>Computer Science - Computer Vision and Pattern Recognition</subject><subject>Computer Science - Computers and Society</subject><subject>Computer Science - Digital Libraries</subject><subject>Computer Science - Learning</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz8FKw0AUBdDZuJDqB7jy_UDSSd5M8uJGStFaCGprQXfhTTKhA2kbJpNi_95aXd0LFy4cIe4SGSvSWk7Zf7tjnGKSxlJnRNfi47UsF7Aa2QfruxOw_3JHWNv-4APIYpriA3xuOZwHC2FrYXcYArh92412Hxx3UI_enyvMlvDOvfXD4424arkb7O1_TsTm-Wkzf4nKt8VyPisjznKKsFEZUpJrRlSZTYzMGza2MAozMlQXeYtWJwobzbVpJBHmWrEqlDZEUuFE3P_dXlRV792O_an61VUXHf4AsY5IBw</recordid><startdate>20231209</startdate><enddate>20231209</enddate><creator>Zhang, Ran</creator><creator>Kostikova, Aida</creator><creator>Leiter, Christoph</creator><creator>Belouadi, Jonas</creator><creator>Larionov, Daniil</creator><creator>Chen, Yanran</creator><creator>Fresen, Vivian</creator><creator>Eger, Steffen</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20231209</creationdate><title>NLLG Quarterly arXiv Report 09/23: What are the most influential current AI Papers?</title><author>Zhang, Ran ; Kostikova, Aida ; Leiter, Christoph ; Belouadi, Jonas ; Larionov, Daniil ; Chen, Yanran ; Fresen, Vivian ; Eger, Steffen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a678-3d4638175a3346e1b07dabe9b4368b8c97f3e5143d5acbd0883754a4945b88043</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Computer Science - Artificial Intelligence</topic><topic>Computer Science - Computation and Language</topic><topic>Computer Science - Computer Vision and Pattern Recognition</topic><topic>Computer Science - Computers and Society</topic><topic>Computer Science - Digital Libraries</topic><topic>Computer Science - Learning</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Ran</creatorcontrib><creatorcontrib>Kostikova, Aida</creatorcontrib><creatorcontrib>Leiter, Christoph</creatorcontrib><creatorcontrib>Belouadi, Jonas</creatorcontrib><creatorcontrib>Larionov, Daniil</creatorcontrib><creatorcontrib>Chen, Yanran</creatorcontrib><creatorcontrib>Fresen, Vivian</creatorcontrib><creatorcontrib>Eger, Steffen</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhang, Ran</au><au>Kostikova, Aida</au><au>Leiter, Christoph</au><au>Belouadi, Jonas</au><au>Larionov, Daniil</au><au>Chen, Yanran</au><au>Fresen, Vivian</au><au>Eger, Steffen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>NLLG Quarterly arXiv Report 09/23: What are the most influential current AI Papers?</atitle><date>2023-12-09</date><risdate>2023</risdate><abstract>Artificial Intelligence (AI) has witnessed rapid growth, especially in the
subfields Natural Language Processing (NLP), Machine Learning (ML) and Computer
Vision (CV). Keeping pace with this rapid progress poses a considerable
challenge for researchers and professionals in the field. In this arXiv report,
the second of its kind, which covers the period from January to September 2023,
we aim to provide insights and analysis that help navigate these dynamic areas
of AI. We accomplish this by 1) identifying the top-40 most cited papers from
arXiv in the given period, comparing the current top-40 papers to the previous
report, which covered the period January to June; 2) analyzing dataset
characteristics and keyword popularity; 3) examining the global sectoral
distribution of institutions to reveal differences in engagement across
geographical areas. Our findings highlight the continued dominance of NLP:
while only 16% of all submitted papers have NLP as primary category (more than
25% have CV and ML as primary category), 50% of the most cited papers have NLP
as primary category, 90% of which target LLMs. Additionally, we show that i)
the US dominates among both top-40 and top-9k papers, followed by China; ii)
Europe clearly lags behind and is hardly represented in the top-40 most cited
papers; iii) US industry is largely overrepresented in the top-40 most
influential papers.</abstract><doi>10.48550/arxiv.2312.05688</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | DOI: 10.48550/arxiv.2312.05688 |
ispartof | |
issn | |
language | eng |
recordid | cdi_arxiv_primary_2312_05688 |
source | arXiv.org |
subjects | Computer Science - Artificial Intelligence Computer Science - Computation and Language Computer Science - Computer Vision and Pattern Recognition Computer Science - Computers and Society Computer Science - Digital Libraries Computer Science - Learning |
title | NLLG Quarterly arXiv Report 09/23: What are the most influential current AI Papers? |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T04%3A26%3A18IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=NLLG%20Quarterly%20arXiv%20Report%2009/23:%20What%20are%20the%20most%20influential%20current%20AI%20Papers?&rft.au=Zhang,%20Ran&rft.date=2023-12-09&rft_id=info:doi/10.48550/arxiv.2312.05688&rft_dat=%3Carxiv_GOX%3E2312_05688%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |