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Meta-learning via language model in-context tuning
The goal of meta-learning is to learn to adapt to a new task with only a few labeled
examples. To tackle this problem in NLP, we propose $\textit {in-context tuning} $, which …
examples. To tackle this problem in NLP, we propose $\textit {in-context tuning} $, which …
[PDF][PDF] XHate-999: Analyzing and detecting abusive language across domains and languages
We present XHATE-999, a multi-domain and multilingual evaluation data set for abusive
language detection. By aligning test instances across six typologically diverse languages …
language detection. By aligning test instances across six typologically diverse languages …
A cross-guidance cross-lingual model on generated parallel corpus for classical Chinese machine reading comprehension
Chinese diachronic gap is a key issue in classical Chinese machine reading
comprehension (CCMRC). Preceding work on bridging this gap has been mostly restricted …
comprehension (CCMRC). Preceding work on bridging this gap has been mostly restricted …
To diverge or not to diverge: A morphosyntactic perspective on machine translation vs human translation
We conduct a large-scale fine-grained comparative analysis of machine translations (MTs)
against human translations (HTs) through the lens of morphosyntactic divergence. Across …
against human translations (HTs) through the lens of morphosyntactic divergence. Across …
Assessing the Cross-linguistic Utility of Abstract Meaning Representation
S Wein, N Schneider - Computational Linguistics, 2024 - direct.mit.edu
Semantic representations capture the meaning of a text. Abstract Meaning Representation
(AMR), a type of semantic representation, focuses on predicate-argument structure and …
(AMR), a type of semantic representation, focuses on predicate-argument structure and …
[PDF][PDF] Classifying syntactic errors in learner language
L Choshen, D Nikolaev, Y Berzak, O Abend - arxiv preprint arxiv …, 2020 - arxiv.org
We present a method for classifying syntactic errors in learner language, namely errors
whose correction alters the morphosyntactic structure of a sentence. The methodology …
whose correction alters the morphosyntactic structure of a sentence. The methodology …
Classifying divergences in cross-lingual AMR pairs
S Wein, N Schneider - Proceedings of The Joint 15th Linguistic …, 2021 - aclanthology.org
Translation divergences are varied and widespread, challenging approaches that rely on
parallel text. To annotate translation divergences, we propose a schema grounded in the …
parallel text. To annotate translation divergences, we propose a schema grounded in the …
PreQuEL: Quality estimation of machine translation outputs in advance
S Don-Yehiya, L Choshen, O Abend - arxiv preprint arxiv:2205.09178, 2022 - arxiv.org
We present the task of PreQuEL, Pre-(Quality-Estimation) Learning. A PreQuEL system
predicts how well a given sentence will be translated, without recourse to the actual …
predicts how well a given sentence will be translated, without recourse to the actual …
Semantics-aware attention improves neural machine translation
A Slobodkin, L Choshen, O Abend - arxiv preprint arxiv:2110.06920, 2021 - arxiv.org
The integration of syntactic structures into Transformer machine translation has shown
positive results, but to our knowledge, no work has attempted to do so with semantic …
positive results, but to our knowledge, no work has attempted to do so with semantic …
Comparing the effect of product-based metrics on the translation process
B Vanroy, M Schaeffer, L Macken - Frontiers in Psychology, 2021 - frontiersin.org
Characteristics of the translation product are often used in translation process research as
predictors for cognitive load, and by extension translation difficulty. In the last decade, user …
predictors for cognitive load, and by extension translation difficulty. In the last decade, user …