📰 Workshop on Evaluating Vector Space Representations for NLP 2019 — accepted papers

Workshop on Evaluating Vector Space Representations for NLP 2019 is the 2019 edition of the Workshop on Evaluating Vector Space Representations for NLP, held in Minneapolis, USA, June 2019 (publisher: Association for Computational Linguistics). OpenAlex lists 13 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. Probing Biomedical Embeddings from Language Models ↗Qiao Jin, Bhuwan Dhingra, William Cohen et al.119 citations
2. CODAH: An Adversarially-Authored Question Answering Dataset for Common SenseMichael Chen, Mike D'Arcy, Alisa Liu et al.42 citations · our summary
3. How Well Do Embedding Models Capture Non-compositionality? A View from Multiword Expressions ↗Navnita Nandakumar, Timothy Baldwin, Bahar Salehi22 citations
4. Neural Vector Conceptualization for Word Vector Space Interpretation ↗Robert Schwarzenberg, Lisa Raithel, David Harbecke11 citations
5. SWOW-8500: Word Association task for Intrinsic Evaluation of Word Embeddings ↗Avijit Thawani, Biplav Srivastava, Anil Singh10 citations
6. The Influence of Down-Sampling Strategies on SVD Word Embedding Stability ↗Johannes Hellrich, Bernd Kampe, Udo Hahn7 citations
7. Classification of Semantic Paraphasias: Optimization of a Word Embedding Model ↗Katy McKinney-Bock, Steven Bedrick6 citations
8. Measuring Semantic Abstraction of Multilingual NMT with Paraphrase Recognition and Generation Tasks ↗Jörg Tiedemann, Yves Scherrer6 citations
9. Dyr Bul Shchyl. Proxying Sound Symbolism With Word Embeddings ↗Ivan P. Yamshchikov, Viascheslav Shibaev, Alexey Tikhonov3 citations
10. Evaluation of Morphological Embeddings for English and Russian Languages ↗Vitaly Romanov, Albina Khusainova3 citations

All accepted papers (13)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. Probing Biomedical Embeddings from Language Models ↗Qiao Jin, Bhuwan Dhingra, William Cohen et al.119 citations
2. CODAH: An Adversarially-Authored Question Answering Dataset for Common SenseMichael Chen, Mike D'Arcy, Alisa Liu et al.42 citations · our summary
3. How Well Do Embedding Models Capture Non-compositionality? A View from Multiword Expressions ↗Navnita Nandakumar, Timothy Baldwin, Bahar Salehi22 citations
4. Neural Vector Conceptualization for Word Vector Space Interpretation ↗Robert Schwarzenberg, Lisa Raithel, David Harbecke11 citations
5. SWOW-8500: Word Association task for Intrinsic Evaluation of Word Embeddings ↗Avijit Thawani, Biplav Srivastava, Anil Singh10 citations
6. The Influence of Down-Sampling Strategies on SVD Word Embedding Stability ↗Johannes Hellrich, Bernd Kampe, Udo Hahn7 citations
7. Classification of Semantic Paraphasias: Optimization of a Word Embedding Model ↗Katy McKinney-Bock, Steven Bedrick6 citations
8. Measuring Semantic Abstraction of Multilingual NMT with Paraphrase Recognition and Generation Tasks ↗Jörg Tiedemann, Yves Scherrer6 citations
9. Dyr Bul Shchyl. Proxying Sound Symbolism With Word Embeddings ↗Ivan P. Yamshchikov, Viascheslav Shibaev, Alexey Tikhonov3 citations
10. Evaluation of Morphological Embeddings for English and Russian Languages ↗Vitaly Romanov, Albina Khusainova3 citations
11. Syntactic Interchangeability in Word Embedding Models ↗Daniel Hershcovich, Assaf Toledo, Alon Halfon et al.3 citations
12. Characterizing the Impact of Geometric Properties of Word Embeddings on Task Performance ↗Brendan Whitaker, Denis Newman-Griffis, Aparajita Haldar et al.
13. Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion ↗Jonathan Mamou, Oren Pereg, Moshe Wasserblat et al.

📄 Papers with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. CODAH: An Adversarially-Authored Question Answering Dataset for Common SenseWorkshop on Evaluating Vector Space Representations for NLPMichael Chen, Mike D'Arcy, Alisa Liu, et al.2019 · 90 citations

🧭 Top topics

Topics of its works in our library, with the number of works on each.

❓Question answering (1)🧮Reasoning (1)

📚 Fields

🎭Arts and Humanities (1)🖥️Computer Science (1)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🎓Northwestern UniversityEvanston · United States1 work here

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

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