Dictionary of rare words
[PDF File] arXiv:1508.07909v5 [cs.CL] 10 Jun 2016
http://5y1.org/file/23441/arxiv-1508-07909v5-cs-cl-10-jun-2016.pdf
translation of out-of-vocabulary words by backing off to a dictionary. In this pa-per, we introduce a simpler and more ef-fective approach, making the NMT model capable of open-vocabulary translation by encoding rare and unknown words as se-quences of subword units. This is based on the intuition that various word classes are
[PDF File] A Simple and Fast Strategy for Handling Rare Words in …
http://5y1.org/file/23441/a-simple-and-fast-strategy-for-handling-rare-words-in.pdf
The rare words are often translated using a manual dictionary or copied from the source to the target with original words. In this paper, we propose a simple and fast strategy for integrating constraints during the training and decoding process to improve the transla-tion of rare words. The effectiveness of our proposal is demonstrated in both ...
[PDF File] Rarest Words In The English Language (2022)
http://5y1.org/file/23441/rarest-words-in-the-english-language-2022.pdf
The new world of words. [&c.]. Discovering English Words Reckonings The Curious Incident of the Dog in the Night-Time The Degrees of Consanguinity and Affinity Described and Delineated Cleopatra and Frankenstein Endangered Words Rare Words in Middle English The Dictionary of Obscure Sorrows A Wrinkle in Time A Glossary and Etymological ...
[PDF File] Chen Zhang, Xiao Liu, Jiuheng Lin, Yansong Feng Abstract
http://5y1.org/file/23441/chen-zhang-xiao-liu-jiuheng-lin-yansong-feng-abstract.pdf
model looks for dictionary entries for rare words in it, and adds them to the prompt directly with the format in this context, the word “[source word]” means “[target word]”. The prompt is adopted in an in-context learning manner, with k demonstra-tions before the current testing instance. DIPMT is designed for languages that current
[PDF File] arXiv:2005.06606v2 [cs.CL] 1 Aug 2020
http://5y1.org/file/23441/arxiv-2005-06606v2-cs-cl-1-aug-2020.pdf
use of a dictionary of subword units to tokenize the target sentences in a more succinct way as a se-quence of M Tsubword units. Given a subword vocabulary, there are multiple ways to segment a rare word into a sequence of subwords (see Fig-ure1). The common practice in neural machine translation considers subword segmentation as a
[PDF File] arXiv:2302.07856v1 [cs.CL] 15 Feb 2023
http://5y1.org/file/23441/arxiv-2302-07856v1-cs-cl-15-feb-2023.pdf
fective solution for rare words as well, by us-ing prior knowledge from bilingual dictionar-ies to provide control hints in the prompts. We propose a novel method, DIPMT, that provides a set of possible translations for a subset of the input words, thereby enabling fine-grained phrase-level prompted control of the LLM. Extensive experiments ...
[PDF File] arXiv:1508.07909v3 [cs.CL] 17 Mar 2016
http://5y1.org/file/23441/arxiv-1508-07909v3-cs-cl-17-mar-2016.pdf
lists of unsegmented words, using subword units only for rare words. As an alternative, we pro-pose a segmentation algorithm based on byte pair encoding (BPE), which lets us learn a vocabulary that provides a good compression rate of the text. 3.2 Byte Pair Encoding (BPE) Byte Pair Encoding (BPE) (Gage, 1994) is a sim-
[PDF File] THE ENDANGERED ILOKANO TERMS - IJSER
http://5y1.org/file/23441/the-endangered-ilokano-terms-ijser.pdf
some selected words to determine their etymology (origin), derivation, and meaning, and their cultural significance. It also attempted to make corpus of vocabulary of cultural significance and occupational terminologies. Furthermore, this paper sought to enrich and promote these terms through the making of an Ilokano dictionary.
[PDF File] Dict-BERT: Enhancing Language Model Pre-training with …
http://5y1.org/file/23441/dict-bert-enhancing-language-model-pre-training-with.pdf
the embeddings of rare words on the tail are usually poorly optimized. In this work, we fo-cus on enhancing language model pre-training by leveraging denitions of the rare words in dictionary. To incorporate a rare word deni-tion as a part of input, we fetch it from the dictionary and append it to the end of the in-put text sequence.
[PDF File] Addressing the Rare Word Problem in Neural Machine …
http://5y1.org/file/23441/addressing-the-rare-word-problem-in-neural-machine.pdf
tion systems has addressed the rare word problem, but the recent work of Jean et al. (2015) has tack-led it with an efcient approximation to the soft-max to accommodate for a very large vocabulary (500K words). However, even with a large vocab-ulary, the problem with rare words, e.g., names, numbers, etc., still persists, and Jean et al. (2015)
[PDF File] Addressing the Rare Word Problem in Neural Machine …
http://5y1.org/file/23441/addressing-the-rare-word-problem-in-neural-machine.pdf
tion systems has addressed the rare word problem, but the recent work of Jean et al. (2015) has tack-led it with an efficient approximation to the soft-max to accommodate for a very large vocabulary (500K words). However, even with a large vocab-ulary, the problem with rare words, e.g., names, numbers, etc., still persists, and Jean et al. (2015)
[PDF File] Dict-BERT: Enhancing Language Model Pre-training with …
http://5y1.org/file/23441/dict-bert-enhancing-language-model-pre-training-with.pdf
Thus, the embeddings of rare words on the tail are usually poorly optimized. In this work, we focus on enhancing language model pre-training by leveraging definitions of the rare words in dictionary. To incorporate a rare word definition as a part of input, we fetch it from the dictionary and append it to the end of the input text sequence.
[PDF File] Neural Machine Translation of Rare Words with Subword Units
http://5y1.org/file/23441/neural-machine-translation-of-rare-words-with-subword-units.pdf
Neural machine translation has recently shown impressive results (Kalchbrenner and Blunsom, 2013; Sutskever et al., 2014; Bahdanau et al., 2015). However, the translation of rare words is an open problem. The vocabulary of neu- ral models is typically limited to 30000 50000 words, but translation is an open-vocabulary prob-.
[PDF File] Neural Machine Translation of Rare Words with Subword Units
http://5y1.org/file/23441/neural-machine-translation-of-rare-words-with-subword-units.pdf
ulary size of 500000 words. However, we will show that translation accuracy is still low for rare words, even if they are in the network vocabulary. The translation of out-of-vocabulary words is addressed in (Jean et al., 2015a; Luong et al., 2015) through a back-off to a dictionary look-up. We note that such techniques make assump-
[PDF File] arXiv:1508.07909v5 [cs.CL] 10 Jun 2016
http://5y1.org/file/23441/arxiv-1508-07909v5-cs-cl-10-jun-2016.pdf
lists of unsegmented words, using subword units only for rare words. As an alternative, we pro-pose a segmentation algorithm based on byte pair encoding (BPE), which lets us learn a vocabulary that provides a good compression rate of the text. 3.2 Byte Pair Encoding (BPE) Byte Pair Encoding (BPE) (Gage, 1994) is a sim-
[PDF File] Prompt Combines Paraphrase: Enhancing Biomedical “Pre …
http://5y1.org/file/23441/prompt-combines-paraphrase-enhancing-biomedical-pre.pdf
155 2) Biomedical rare words can be worth more than 156 general rare words to biomedical tasks. To ob-157 tain rare words, we set a threshold on the word 158 frequency in the pre-training corpora empirically 159 as a hyper-parameter similar toYu et al.(2021). 160 Afterwards, with the help of an online dictionary 161 - Wiktionary3, we can ...
[PDF File] arXiv:1508.07909v2 [cs.CL] 27 Nov 2015
http://5y1.org/file/23441/arxiv-1508-07909v2-cs-cl-27-nov-2015.pdf
model for the translation of rare words. In addi-tion to making the translation process simpler, we also find that the subword models achieve better accuracy for the translation of rare words than a back-off dictionary, and are able to productively generate new words that were not seen at training time. Our analysis shows that the neural networks
[PDF File] Neural Machine Translation of Rare Words with Subword Units
http://5y1.org/file/23441/neural-machine-translation-of-rare-words-with-subword-units.pdf
The neural machine translation system is imple-mented as an encoder-decoder network with recur-rent neural networks. The encoder is a bidirectional neural network with gated recurrent units (Cho ...
[PDF File] arXiv:2209.06453v1 [cs.CL] 14 Sep 2022
http://5y1.org/file/23441/arxiv-2209-06453v1-cs-cl-14-sep-2022.pdf
rare biomedical words with the prompt-based tun-ing of pre-trained models in a model-agnostic plug-in manner. 3.1 Rare Words The rarity of a word mostly depends on its fre-quency in a certain corpus, which can vary from context to context. A rare word in the pre-training corpora is possibly not that rare in the down-stream tasks. In this work ...
[PDF File] GPT Perdetry Test: Generating new meanings for new words
http://5y1.org/file/23441/gpt-perdetry-test-generating-new-meanings-for-new-words.pdf
by GPT-3, for fake words, or extracted from the dictionary, for rare words), but not told which defi-nition matches with which word.4 Some questions contained two fake words, some two rare words, and some one fake and one rare word. Users were asked to decide which assignment of definitions to words is a better fit and to rate their confidence
[PDF File] Are Llamas Sesquipedalian? Analyzing Rare Words in Large …
http://5y1.org/file/23441/are-llamas-sesquipedalian-analyzing-rare-words-in-large.pdf
This dictionary maps frequent 189 words to rare/medium words that are synonyms 190 (from the same synset in WordNet). Similar to the 191 approach in (Schick and Schütze,2019b), we take 192 the most common sense of each frequent word, and 193 ensure that the corresponding rare/medium words 194 share the same parts of speech. Then, using the
[PDF File] WHAT IS THE TASK REPRESENTED BY RARE VOCABULARY IN …
http://5y1.org/file/23441/what-is-the-task-represented-by-rare-vocabulary-in.pdf
For both genres, rare words in Levels 1 & 2 comprise about 20 – 24% of rare word types in the early grades and increase steadily to about 40% in the highest grades. Nearly 50% of the words in narrative texts are from rare morphological families in …
[PDF File] Dict-BERT: Enhancing Language Model Pre-training with …
http://5y1.org/file/23441/dict-bert-enhancing-language-model-pre-training-with.pdf
Thus, the embeddings of rare words on the tail are usually poorly optimized. In this work, we focus on enhancing language model pre-training by leveraging definitions of the rare words in dictionary. To incorporate a rare word definition as a part of input, we fetch it from the dictionary and append it to the end of the input text sequence.
[PDF File] arXiv:1909.07907v1 [cs.CL] 17 Sep 2019
http://5y1.org/file/23441/arxiv-1909-07907v1-cs-cl-17-sep-2019.pdf
Another problem is one of rare words. Syn-thesising datasets with desirable rare-word distri-bution is also non-trivial and much harder than identifying and translating rare words in isolation. Storing rare word translations in bilingual dictio-nary is a convenient way to deal with this issue but is largely ignored in contemporary NMT systems.
[PDF File] The Oxford 3000™ - Oxford Learner's Dictionaries
http://5y1.org/file/23441/the-oxford-3000-oxford-learner-s-dictionaries.pdf
The Oxford 3000 is the list of the 3000 most important words to learn in English, from A1 to B2 level. a, an indefinite article A1 abandon v. B2 ability n. A2 able adj. A2 about prep., adv. A1 above prep., adv. A1 abroad adv. A2 absolute adj. B2 absolutely adv. B1 academic adj.B1, n. B2 accept v. A2 acceptable adj. B2 access n., v. B1 accident ...
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