The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Confidence estimation for machine translation
Open accessAbstract
We present a detailed study of confidence estimation for machine translation. Various methods for determining whether MT output is correct are investigated, for both whole sentences and words. Since the notion of correctness is not intuitively clear in this context, different ways of defining it are proposed. We present results on data from the NIST 2003 Chinese-to-English MT evaluation.
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An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
(1990) · Choice Reviews Online · doi:10.5860/choice.27-3338 · Cited by 35,305
Multilayer feedforward networks are universal approximators
Hornik, K., Stinchcombe, M., & White, H. (1989) · Neural Networks · doi:10.1016/0893-6080(89)90020-8 · Cited by 21,728
BLEU: a method for automatic evaluation of machine translation
Papineni, K., Roukos, S., Ward, T., & Zhu, W.-J. (2001) · Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02 · doi:10.3115/1073083.1073135 · Cited by 21,344
Neural networks for pattern recognition
(1994) · Choice Reviews Online · doi:10.5860/choice.31-5500 · Cited by 18,538
Multilayer feedforward networks are universal approximators
HornikK., StinchcombeM., & WhiteH. (1989) · Neural Networks · doi:10.5555/70405.70408 · Cited by 9,081
Wolpert, D. H. (1992) · Neural Networks · doi:10.1016/s0893-6080(05)80023-1 · Cited by 7,951
The mathematics of statistical machine translation: parameter estimation
Brown, P. F., Pietra, V. J. D., Pietra, S. A. D., & Mercer, R. L. (1993) · Cited by 3,973
Using Information Content to Evaluate Semantic Similarity in a Taxonomy
Resnik, P. (1995) · arXiv (Cornell University) · doi:10.48550/arxiv.cmp-lg/9511007 · Cited by 3,193
Mathematical Statistics and Data Analysis
Rabinowitz, L. (1989) · Technometrics · doi:10.1080/00401706.1989.10488573 · Cited by 3,116
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CLIPScore: A Reference-free Evaluation Metric for Image Captioning
Hessel, J., Holtzman, A., Forbes, M., Le Bras, R., & Choi, Y. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2021.emnlp-main.595 · Cited by 1,232
Meteor: an automatic metric for MT evaluation with high levels of correlation with human judgments
Lavie, A., & Agarwal, A. (2007) · Proceedings of the Second Workshop on Statistical Machine Translation - StatMT '07 · doi:10.3115/1626355.1626389 · Cited by 1,047
(Meta-) evaluation of machine translation
Callison-Burch, C., Fordyce, C., Koehn, P., Monz, C., & Schroeder, J. (2007) · Proceedings of the Second Workshop on Statistical Machine Translation - StatMT '07 · doi:10.3115/1626355.1626373 · Cited by 379
Towards a Better Metric for Evaluating Question Generation Systems
Nema, P., & Khapra, M. M. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d18-1429 · Cited by 106
Evaluating Question Answering Evaluation
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Metadata
- Authors
- Blatz, J., Fitzgerald, E., Foster, G., Gandrabur, S., Goutte, C., Kulesza, A., Sanchis, A., & Ueffing, N.
- Venue
- Proceedings of the 20th international conference on Computational Linguistics - COLING '04
- Published
- 2004
- Pages
- 315-es
- ISSN
- 1525-2477 (ISSN-L)
- OpenAlex
- W2144746247
- Cited by
- 351
- References
- 30
- FWCI
- 7.59
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Blatz, J., Fitzgerald, E., Foster, G., Gandrabur, S., Goutte, C., Kulesza, A., Sanchis, A., & Ueffing, N. (2004). Confidence estimation for machine translation. Proceedings of the 20th international conference on Computational Linguistics - COLING '04. https://doi.org/10.3115/1220355.1220401
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