The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
SemEval-2014 Task 10: Multilingual Semantic Textual Similarity
Open accessAbstract
Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Rada Mihalcea, German Rigau, Janyce Wiebe. Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). 2014.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
WordNet: An Electronic Lexical Database
Kilgarriff, A., & Fellbaum, C. (2000) · Language · doi:10.2307/417141 · Cited by 11,464
An Information-Theoretic Definition of Similarity
Lin, D. (1998) · Cited by 3,790
Verbs semantics and lexical selection
Wu, Z., & Palmer, M. (1994) · Proceedings of the 32nd annual meeting on Association for Computational Linguistics - · doi:10.3115/981732.981751 · Cited by 3,136
Combining Local Context and WordNet Similarity for Word Sense Identification
Leacock, C. (1998) · WordNet · doi:10.7551/mitpress/7287.003.0018 · Cited by 1,662
Hovy, E., Marcus, M., Palmer, M., Ramshaw, L., & Weischedel, R. (2006) · Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX - NAACL '06 · doi:10.3115/1614049.1614064 · Cited by 806
Grounded Compositional Semantics for Finding and Describing Images with Sentences
Socher, R., Karpathy, A., Le, Q. V., Manning, C. D., & Ng, A. Y. (2014) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00177 · Cited by 777
SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity
Agirre, E., Cer, D. M., Diab, M., & González-Agirre, A. (2012) · Cited by 649
Self-citationCollecting Image Annotations Using Amazon's Mechanical Turk
Rashtchian, C., Young, P., Hodosh, M., & Hockenmaier, J. (2010) · Cited by 541
Landauer, T. K., Laham, D., Rehder, B., & Schreiner, M. (1997) · Cited by 274
TakeLab: Systems for Measuring Semantic Text Similarity
Šarić, F., Glavaš, G., Karan, M., Šnajder, J., & Bašić, B. D. (2012) · MADOC (University of Mannheim) · Cited by 198
Cited by
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Reimers, N., & Gurevych, I. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · doi:10.18653/v1/d19-1410 · Cited by 12,778
SimCSE: Simple Contrastive Learning of Sentence Embeddings
Gao, T., Yao, X., & Chen, D. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2021.emnlp-main.552 · Cited by 2,851
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
Conneau, A., Kiela, D., Schwenk, H., Barrault, L., & Bordes, A. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d17-1070 · Cited by 2,049
A Survey of the Usages of Deep Learning for Natural Language Processing
Otter, D. W., Medina, J. R., & Kalita, J. K. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.2979670 · Cited by 1,836
Ethayarajh, K. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · doi:10.18653/v1/d19-1006 · Cited by 841
Metadata
- Authors
- Agirre, E., Banea, C., Cardie, C., Cer, D., Diab, M., Gonzalez-Agirre, A., Guo, W., Mihalcea, R., Rigau, G., & Wiebe, J.
- Venue
- Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)
- Published
- 2014
- Pages
- 81-91
- OpenAlex
- W2126400076
- Cited by
- 490
- References
- 16
- FWCI
- 20.75
- Type
- conference paper
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: SemEval-2014 Task 10: Multilingual Semantic Textual Similarity. https://app.cochat.ai/papers/10.3115/v1/s14-2010
- The paper
- Agirre, E., Banea, C., Cardie, C., Cer, D., Diab, M., Gonzalez-Agirre, A., Guo, W., Mihalcea, R., Rigau, G., & Wiebe, J. (2014). SemEval-2014 Task 10: Multilingual Semantic Textual Similarity. Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). https://doi.org/10.3115/v1/s14-2010
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
