default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDGabriel Stanovsky
Gabi Stanovsky
Person information
- affiliation: The Hebrew University of Jerusalem, Israel
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j2]Moran Mizrahi, Guy Kaplan, Dan Malkin, Rotem Dror, Dafna Shahaf, Gabriel Stanovsky:
State of What Art? A Call for Multi-Prompt LLM Evaluation. Trans. Assoc. Comput. Linguistics 12: 933-949 (2024)- [c53]Ariel Goldstein, Gabriel Stanovsky:
Do Zombies Understand? A Choose-Your-Own-Adventure Exploration of Machine Cognition. ACL (Findings) 2024: 7137-7143 - [c52]Gili Lior, Yoav Goldberg, Gabriel Stanovsky:
Leveraging Collection-Wide Similarities for Unsupervised Document Structure Extraction. ACL (Findings) 2024: 9538-9550 - [c51]Itay Manes, Naama Ronn, David Cohen, Ran Ilan Ber, Zehavi Horowitz-Kugler, Gabriel Stanovsky:
K-QA: A Real-World Medical Q&A Benchmark. BioNLP@ACL 2024: 277-294 - [c50]Fan Bai, Junmo Kang, Gabriel Stanovsky, Dayne Freitag, Mark Dredze, Alan Ritter:
Schema-Driven Information Extraction from Heterogeneous Tables. EMNLP (Findings) 2024: 10252-10273 - [c49]Bar Iluz, Yanai Elazar, Asaf Yehudai, Gabriel Stanovsky:
Applying Intrinsic Debiasing on Downstream Tasks: Challenges and Considerations for Machine Translation. EMNLP 2024: 14914-14921 - [i48]Moran Mizrahi, Guy Kaplan, Dan Malkin, Rotem Dror, Dafna Shahaf, Gabriel Stanovsky:
State of What Art? A Call for Multi-Prompt LLM Evaluation. CoRR abs/2401.00595 (2024) - [i47]Itay Manes, Naama Ronn, David Cohen, Ran Ilan Ber, Zehavi Horowitz-Kugler, Gabriel Stanovsky:
K-QA: A Real-World Medical Q&A Benchmark. CoRR abs/2401.14493 (2024) - [i46]Gili Lior, Yoav Goldberg, Gabriel Stanovsky:
Leveraging Collection-Wide Similarities for Unsupervised Document Structure Extraction. CoRR abs/2402.13906 (2024) - [i45]Ariel Goldstein, Gabriel Stanovsky:
Do Zombies Understand? A Choose-Your-Own-Adventure Exploration of Machine Cognition. CoRR abs/2403.00499 (2024) - [i44]Asaf Yehudai, Taelin Karidi, Gabriel Stanovsky, Ariel Goldstein, Omri Abend:
A Nurse is Blue and Elephant is Rugby: Cross Domain Alignment in Large Language Models Reveal Human-like Patterns. CoRR abs/2405.14863 (2024) - [i43]Bar Iluz, Yanai Elazar, Asaf Yehudai, Gabriel Stanovsky:
Applying Intrinsic Debiasing on Downstream Tasks: Challenges and Considerations for Machine Translation. CoRR abs/2406.00787 (2024) - [i42]Uri Berger, Tal Baumel, Gabriel Stanovsky:
In-Context Learning on a Budget: A Case Study in Named Entity Recognition. CoRR abs/2406.13274 (2024) - [i41]Gili Lior, Avi Caciularu, Arie Cattan, Shahar Levy, Ori Shapira, Gabriel Stanovsky:
SEAM: A Stochastic Benchmark for Multi-Document Tasks. CoRR abs/2406.16086 (2024) - [i40]Uri Berger, Gabriel Stanovsky, Omri Abend, Lea Frermann:
Surveying the Landscape of Image Captioning Evaluation: A Comprehensive Taxonomy and Novel Ensemble Method. CoRR abs/2408.04909 (2024) - 2023
- [c48]Yonatan Bitton, Ron Yosef, Eliyahu Strugo, Dafna Shahaf, Roy Schwartz, Gabriel Stanovsky:
VASR: Visual Analogies of Situation Recognition. AAAI 2023: 241-249 - [c47]Catherine Chen, Zejiang Shen, Dan Klein, Gabriel Stanovsky, Doug Downey, Kyle Lo:
Are Layout-Infused Language Models Robust to Layout Distribution Shifts? A Case Study with Scientific Documents. ACL (Findings) 2023: 13345-13360 - [c46]Gili Lior, Gabriel Stanovsky:
Comparing Humans and Models on a Similar Scale: Towards Cognitive Gender Bias Evaluation in Coreference Resolution. CogSci 2023 - [c45]Asaf Yehudai, Arie Cattan, Omri Abend, Gabriel Stanovsky:
Evaluating and Improving the Coreference Capabilities of Machine Translation Models. EACL 2023: 980-992 - [c44]Uri Berger, Lea Frermann, Gabriel Stanovsky, Omri Abend:
A Large-Scale Multilingual Study of Visual Constraints on Linguistic Selection of Descriptions. EACL (Findings) 2023: 2240-2254 - [c43]Eliya Habba
, Renana Keydar, Dan Bareket, Gabriel Stanovsky:
The Perfect Victim: Computational Analysis of Judicial Attitudes towards Victims of Sexual Violence. ICAIL 2023: 111-120 - [c42]Nitzan Bitton Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, Roy Schwartz:
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images. ICCV 2023: 2616-2627 - [c41]Bar Iluz, Tomasz Limisiewicz, Gabriel Stanovsky, David Marecek:
Exploring the Impact of Training Data Distribution and Subword Tokenization on Gender Bias in Machine Translation. IJCNLP (1) 2023: 885-896 - [i39]Uri Berger, Lea Frermann, Gabriel Stanovsky, Omri Abend:
A Large-Scale Multilingual Study of Visual Constraints on Linguistic Selection of Descriptions. CoRR abs/2302.04811 (2023) - [i38]Asaf Yehudai, Arie Cattan, Omri Abend, Gabriel Stanovsky:
Evaluating and Improving the Coreference Capabilities of Machine Translation Models. CoRR abs/2302.08464 (2023) - [i37]Nitzan Bitton Guetta, Yonatan Bitton, Jack Hessel, Ludwig Schmidt, Yuval Elovici, Gabriel Stanovsky, Roy Schwartz:
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images. CoRR abs/2303.07274 (2023) - [i36]Eliya Habba, Renana Keydar, Dan Bareket, Gabriel Stanovsky:
The Perfect Victim: Computational Analysis of Judicial Attitudes towards Victims of Sexual Violence. CoRR abs/2305.05302 (2023) - [i35]Fan Bai, Junmo Kang, Gabriel Stanovsky, Dayne Freitag, Alan Ritter:
Schema-Driven Information Extraction from Heterogeneous Tables. CoRR abs/2305.14336 (2023) - [i34]Gili Lior, Gabriel Stanovsky:
Comparing Humans and Models on a Similar Scale: Towards Cognitive Gender Bias Evaluation in Coreference Resolution. CoRR abs/2305.15389 (2023) - [i33]Catherine Chen, Zejiang Shen, Dan Klein, Gabriel Stanovsky, Doug Downey, Kyle Lo:
Are Layout-Infused Language Models Robust to Layout Distribution Shifts? A Case Study with Scientific Documents. CoRR abs/2306.01058 (2023) - [i32]Itay Itzhak, Gabriel Stanovsky, Nir Rosenfeld, Yonatan Belinkov:
Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias. CoRR abs/2308.00225 (2023) - [i31]Bar Iluz, Tomasz Limisiewicz, Gabriel Stanovsky, David Marecek:
Exploring the Impact of Training Data Distribution and Subword Tokenization on Gender Bias in Machine Translation. CoRR abs/2309.12491 (2023) - 2022
- [c40]Keshav Kolluru, Gabriel Stanovsky, Mausam:
"Covid vaccine is against Covid but Oxford vaccine is made at Oxford!" Semantic Interpretation of Proper Noun Compounds. EMNLP 2022: 10407-10420 - [c39]Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith, Daniel S. Weld:
GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation. EMNLP 2022: 11444-11458 - [c38]Roy Schwartz, Gabriel Stanovsky:
On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations. NAACL-HLT (Findings) 2022: 2182-2194 - [c37]Uri Berger, Gabriel Stanovsky, Omri Abend, Lea Frermann:
A Computational Acquisition Model for Multimodal Word Categorization. NAACL-HLT 2022: 3819-3835 - [c36]Dan Malkin, Tomasz Limisiewicz, Gabriel Stanovsky:
A Balanced Data Approach for Evaluating Cross-Lingual Transfer: Mapping the Linguistic Blood Bank. NAACL-HLT 2022: 4903-4915 - [c35]Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef, Yuval Elovici, Mohit Bansal, Gabriel Stanovsky, Roy Schwartz:
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models. NeurIPS 2022 - [c34]Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022). SemEval@NAACL 2022 - [e1]Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan:
Proceedings of the 16th International Workshop on Semantic Evaluation, SemEval@NAACL 2022, Seattle, Washington, United States, July 14-15, 2022. Association for Computational Linguistics 2022, ISBN 978-1-955917-80-3 [contents] - [i30]Roy Schwartz, Gabriel Stanovsky:
On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations. CoRR abs/2204.12708 (2022) - [i29]Dan Malkin, Tomasz Limisiewicz, Gabriel Stanovsky:
A Balanced Data Approach for Evaluating Cross-Lingual Transfer: Mapping the Linguistic Blood Bank. CoRR abs/2205.04086 (2022) - [i28]Uri Berger, Gabriel Stanovsky, Omri Abend, Lea Frermann:
A Computational Acquisition Model for Multimodal Word Categorization. CoRR abs/2205.05974 (2022) - [i27]Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef, Yuval Elovici, Mohit Bansal, Gabriel Stanovsky, Roy Schwartz:
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models. CoRR abs/2207.12576 (2022) - [i26]Tomasz Limisiewicz, Dan Malkin, Gabriel Stanovsky:
You Can Have Your Data and Balance It Too: Towards Balanced and Efficient Multilingual Models. CoRR abs/2210.07135 (2022) - [i25]Keshav Kolluru, Gabriel Stanovsky, Mausam:
"Covid vaccine is against Covid but Oxford vaccine is made at Oxford!" Semantic Interpretation of Proper Noun Compounds. CoRR abs/2210.13039 (2022) - [i24]Yonatan Bitton, Ron Yosef, Eli Strugo, Dafna Shahaf, Roy Schwartz, Gabriel Stanovsky:
VASR: Visual Analogies of Situation Recognition. CoRR abs/2212.04542 (2022) - 2021
- [j1]Lucy Lu Wang, Gabriel Stanovsky, Luca Weihs, Oren Etzioni:
Gender trends in computer science authorship. Commun. ACM 64(3): 78-84 (2021) - [c33]Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan:
Cross-document Coreference Resolution over Predicted Mentions. ACL/IJCNLP (Findings) 2021: 5100-5107 - [c32]Mohr Wenger, Tom Kalir, Noga Berger, Carmit Klar Chalamish, Renana Keydar, Gabriel Stanovsky:
Automated Extraction of Sentencing Decisions from Court Cases in the Hebrew Language. NLLP@EMNLP 2021: 36-45 - [c31]Ronen Tamari, Fan Bai, Alan Ritter, Gabriel Stanovsky:
Process-Level Representation of Scientific Protocols with Interactive Annotation. EACL 2021: 2190-2202 - [c30]Shahar Levy, Koren Lazar, Gabriel Stanovsky:
Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation. EMNLP (Findings) 2021: 2470-2480 - [c29]Yonatan Bitton, Michael Elhadad, Gabriel Stanovsky, Roy Schwartz:
Data Efficient Masked Language Modeling for Vision and Language. EMNLP (Findings) 2021: 3013-3028 - [c28]Koren Lazar, Benny Saret, Asaf Yehudai, Wayne Horowitz, Nathan Wasserman, Gabriel Stanovsky:
Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach. EMNLP (1) 2021: 4682-4691 - [c27]Yonatan Bitton, Gabriel Stanovsky, Roy Schwartz, Michael Elhadad:
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA. NAACL-HLT 2021: 94-105 - [c26]Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan:
Realistic Evaluation Principles for Cross-document Coreference Resolution. *SEM 2021: 143-151 - [i23]Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith, Daniel S. Weld:
GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation. CoRR abs/2101.06561 (2021) - [i22]Ronen Tamari, Fan Bai, Alan Ritter, Gabriel Stanovsky:
Process-Level Representation of Scientific Protocols with Interactive Annotation. CoRR abs/2101.10244 (2021) - [i21]Yonatan Bitton, Gabriel Stanovsky, Roy Schwartz, Michael Elhadad:
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA. CoRR abs/2103.09591 (2021) - [i20]Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan:
Cross-document Coreference Resolution over Predicted Mentions. CoRR abs/2106.01210 (2021) - [i19]Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan:
Realistic Evaluation Principles for Cross-document Coreference Resolution. CoRR abs/2106.04192 (2021) - [i18]Yonatan Bitton, Gabriel Stanovsky, Michael Elhadad, Roy Schwartz:
Data Efficient Masked Language Modeling for Vision and Language. CoRR abs/2109.02040 (2021) - [i17]Shahar Levy, Koren Lazar, Gabriel Stanovsky:
Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation. CoRR abs/2109.03858 (2021) - [i16]Koren Lazar, Benny Saret, Asaf Yehudai, Wayne Horowitz, Nathan Wasserman, Gabriel Stanovsky:
Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach. CoRR abs/2109.04513 (2021) - [i15]Mohr Wenger, Tom Kalir, Noga Berger, Carmit Klar Chalamish, Renana Keydar, Gabriel Stanovsky:
Automated Extraction of Sentencing Decisions from Court Cases in the Hebrew Language. CoRR abs/2110.12383 (2021) - 2020
- [c25]Roy Schwartz, Gabriel Stanovsky, Swabha Swayamdipta, Jesse Dodge, Noah A. Smith:
The Right Tool for the Job: Matching Model and Instance Complexities. ACL 2020: 6640-6651 - [c24]Paul Roit, Ayal Klein, Daniela Stepanov, Jonathan Mamou, Julian Michael, Gabriel Stanovsky, Luke Zettlemoyer, Ido Dagan:
Controlled Crowdsourcing for High-Quality QA-SRL Annotation. ACL 2020: 7008-7013 - [c23]Belinda Z. Li, Gabriel Stanovsky, Luke Zettlemoyer:
Active Learning for Coreference Resolution using Discrete Annotation. ACL 2020: 8320-8331 - [c22]Anthony Chen, Gabriel Stanovsky, Sameer Singh, Matt Gardner:
MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics. EMNLP (1) 2020: 6521-6532 - [c21]Tom Kocmi, Tomasz Limisiewicz, Gabriel Stanovsky:
Gender Coreference and Bias Evaluation at WMT 2020. WMT@EMNLP 2020: 357-364 - [i14]Ronen Tamari, Gabriel Stanovsky, Dafna Shahaf, Reut Tsarfaty:
Ecological Semantics: Programming Environments for Situated Language Understanding. CoRR abs/2003.04567 (2020) - [i13]Roy Schwartz, Gabi Stanovsky, Swabha Swayamdipta, Jesse Dodge, Noah A. Smith:
The Right Tool for the Job: Matching Model and Instance Complexities. CoRR abs/2004.07453 (2020) - [i12]Belinda Z. Li, Gabriel Stanovsky, Luke Zettlemoyer:
Active Learning for Coreference Resolution using Discrete Annotation. CoRR abs/2004.13671 (2020) - [i11]Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan:
Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling. CoRR abs/2009.11032 (2020) - [i10]Anthony Chen, Gabriel Stanovsky, Sameer Singh, Matt Gardner:
MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics. CoRR abs/2010.03636 (2020) - [i9]Tom Kocmi, Tomasz Limisiewicz, Gabriel Stanovsky:
Gender Coreference and Bias Evaluation at WMT 2020. CoRR abs/2010.06018 (2020)
2010 – 2019
- 2019
- [c20]Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer:
Evaluating Gender Bias in Machine Translation. ACL (1) 2019: 1679-1684 - [c19]Anthony Chen, Gabriel Stanovsky, Sameer Singh, Matt Gardner:
Evaluating Question Answering Evaluation. MRQA@EMNLP 2019: 119-124 - [c18]Gabriel Stanovsky, Ronen Tamari:
Y'all should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts. W-NUT@EMNLP 2019: 375-380 - [c17]Omri Koshorek, Gabriel Stanovsky, Yichu Zhou, Vivek Srikumar, Jonathan Berant:
On the Limits of Learning to Actively Learn Semantic Representations. CoNLL 2019: 452-462 - [c16]Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, Matt Gardner:
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. NAACL-HLT (1) 2019: 2368-2378 - [c15]Mark Hopkins, Ronan Le Bras, Cristian Petrescu-Prahova, Gabriel Stanovsky, Hannaneh Hajishirzi, Rik Koncel-Kedziorski:
SemEval-2019 Task 10: Math Question Answering. SemEval@NAACL-HLT 2019: 893-899 - [i8]Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, Matt Gardner:
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. CoRR abs/1903.00161 (2019) - [i7]Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer:
Evaluating Gender Bias in Machine Translation. CoRR abs/1906.00591 (2019) - [i6]Lucy Lu Wang, Gabriel Stanovsky, Luca Weihs, Oren Etzioni:
Gender trends in computer science authorship. CoRR abs/1906.07883 (2019) - [i5]Omri Koshorek, Gabriel Stanovsky, Yichu Zhou, Vivek Srikumar, Jonathan Berant:
On the Limits of Learning to Actively Learn Semantic Representations. CoRR abs/1910.02228 (2019) - [i4]Gabriel Stanovsky, Ronen Tamari:
Yall should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts. CoRR abs/1910.11966 (2019) - [i3]Paul Roit, Ayal Klein, Daniela Stepanov, Jonathan Mamou, Julian Michael, Gabriel Stanovsky, Luke Zettlemoyer, Ido Dagan:
Crowdsourcing a High-Quality Gold Standard for QA-SRL. CoRR abs/1911.03243 (2019) - 2018
- [c14]Gabriel Stanovsky, Mark Hopkins:
Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources. EMNLP 2018: 1533-1542 - [c13]Gabriel Stanovsky, Ido Dagan:
Semantics as a Foreign Language. EMNLP 2018: 2412-2421 - [c12]Julian Michael, Gabriel Stanovsky, Luheng He, Ido Dagan, Luke Zettlemoyer:
Crowdsourcing Question-Answer Meaning Representations. NAACL-HLT (2) 2018: 560-568 - [c11]Gabriel Stanovsky, Julian Michael, Luke Zettlemoyer, Ido Dagan:
Supervised Open Information Extraction. NAACL-HLT 2018: 885-895 - 2017
- [c10]Gabriel Stanovsky, Judith Eckle-Kohler, Yevgeniy Puzikov, Ido Dagan, Iryna Gurevych:
Integrating Deep Linguistic Features in Factuality Prediction over Unified Datasets. ACL (2) 2017: 352-357 - [c9]Rachel Wities, Vered Shwartz, Gabriel Stanovsky, Meni Adler, Ori Shapira, Shyam Upadhyay, Dan Roth, Eugenio Martínez-Cámara, Iryna Gurevych, Ido Dagan:
A Consolidated Open Knowledge Representation for Multiple Texts. LSDSem@EACL 2017: 12-24 - [c8]Gabriel Stanovsky, Daniel Gruhl, Pablo N. Mendes:
Recognizing Mentions of Adverse Drug Reaction in Social Media Using Knowledge-Infused Recurrent Models. EACL (1) 2017: 142-151 - [c7]Vered Shwartz, Gabriel Stanovsky, Ido Dagan:
Acquiring Predicate Paraphrases from News Tweets. *SEM 2017: 155-160 - [i2]Julian Michael, Gabriel Stanovsky, Luheng He, Ido Dagan, Luke Zettlemoyer:
Crowdsourcing Question-Answer Meaning Representations. CoRR abs/1711.05885 (2017) - 2016
- [c6]Gabriel Stanovsky, Ido Dagan:
Annotating and Predicting Non-Restrictive Noun Phrase Modifications. ACL (1) 2016 - [c5]Gabriel Stanovsky, Ido Dagan, Meni Adler:
Specifying and Annotating Reduced Argument Span Via QA-SRL. ACL (2) 2016 - [c4]Omer Levy, Ido Dagan, Gabriel Stanovsky, Judith Eckle-Kohler, Iryna Gurevych:
Modeling Extractive Sentence Intersection via Subtree Entailment. COLING 2016: 2891-2901 - [c3]Tobias Falke, Gabriel Stanovsky, Iryna Gurevych, Ido Dagan:
Porting an Open Information Extraction System from English to German. EMNLP 2016: 892-898 - [c2]Gabriel Stanovsky, Ido Dagan:
Creating a Large Benchmark for Open Information Extraction. EMNLP 2016: 2300-2305 - [i1]Gabriel Stanovsky, Jessica Ficler, Ido Dagan, Yoav Goldberg:
Getting More Out Of Syntax with PropS. CoRR abs/1603.01648 (2016) - 2015
- [c1]Gabriel Stanovsky, Ido Dagan, Mausam:
Open IE as an Intermediate Structure for Semantic Tasks. ACL (2) 2015: 303-308
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-15 19:30 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
