Experimental results on two benchmark datasets demonstrate that XNLI models enhanced by our proposed framework significantly outperform original ones under both the full-shot and few-shot cross-lingual transfer settings. Linguistic term for a misleading cognate crossword solver. 2), show that DSGFNet outperforms existing methods. Detecting biased language is useful for a variety of applications, such as identifying hyperpartisan news sources or flagging one-sided rhetoric. Our source code is available at Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech. Experiment results show that our model produces better question-summary hierarchies than comparisons on both hierarchy quality and content coverage, a finding also echoed by human judges.
Simile interpretation (SI) and simile generation (SG) are challenging tasks for NLP because models require adequate world knowledge to produce predictions. Synthetic translations have been used for a wide range of NLP tasks primarily as a means of data augmentation. That would seem to be a reasonable assumption, but not necessarily a true one. We propose a novel approach that jointly utilizes the labels and elicited rationales for text classification to speed up the training of deep learning models with limited training data. Prodromos Malakasiotis. Through the analysis of annotators' behaviors, we figure out the underlying reason for the problems above: the scheme actually discourages annotators from supplementing adequate instances in the revision phase. Examples of false cognates in english. In terms of mean reciprocal rank (MRR), we advance the state-of-the-art by +19% on WN18RR, +6. Although several studies in the past have highlighted the limitations of ROUGE, researchers have struggled to reach a consensus on a better alternative until today. Overall, the results of these evaluations suggest that rule-based systems with simple rule sets achieve on-par or better performance on both datasets compared to state-of-the-art neural REG systems. Since no existing knowledge grounded dialogue dataset considers this aim, we augment the existing dataset with unanswerable contexts to conduct our experiments.
We confirm our hypothesis empirically: MILIE outperforms SOTA systems on multiple languages ranging from Chinese to Arabic. A Rationale-Centric Framework for Human-in-the-loop Machine Learning. This paper presents a momentum contrastive learning model with negative sample queue for sentence embedding, namely MoCoSE. The intrinsic complexity of these tasks demands powerful learning models. To explain this discrepancy, through a toy theoretical example and empirical analysis on two crowdsourced CAD datasets, we show that: (a) while features perturbed in CAD are indeed robust features, it may prevent the model from learning unperturbed robust features; and (b) CAD may exacerbate existing spurious correlations in the data. Then, the informative tokens serve as the fine-granularity computing units in self-attention and the uninformative tokens are replaced with one or several clusters as the coarse-granularity computing units in self-attention. In this paper, we study whether and how contextual modeling in DocNMT is transferable via multilingual modeling. Self-distilled pruned models also outperform smaller Transformers with an equal number of parameters and are competitive against (6 times) larger distilled networks. Linguistic term for a misleading cognate crossword daily. Auxiliary experiments further demonstrate that FCLC is stable to hyperparameters and it does help mitigate confirmation bias. Semantic parsers map natural language utterances into meaning representations (e. g., programs). Our model is further enhanced by tweaking its loss function and applying a post-processing re-ranking algorithm that improves overall test structure.
Through a well-designed probing experiment, we empirically validate that the bias of TM models can be attributed in part to extracting the text length information during training. By this interpretation Babel would still legitimately be considered the place in which the confusion of languages occurred since it was the place from which the process of language differentiation was initiated, or at least the place where a state of mutual intelligibility began to decline through a dispersion of the people. To fill this gap, we introduce preference-aware LID and propose a novel unsupervised learning strategy. Aligned Weight Regularizers for Pruning Pretrained Neural Networks. Our approach complements the traditional approach of using a Wikipedia anchor-text dictionary, enabling us to further design a highly effective hybrid method for candidate retrieval. Using Cognates to Develop Comprehension in English. We show that a significant portion of errors in such systems arise from asking irrelevant or un-interpretable questions and that such errors can be ameliorated by providing summarized input.
Results on code-switching sets demonstrate the capability of our approach to improve model generalization to out-of-distribution multilingual examples. Language Correspondences | Language and Communication: Essential Concepts for User Interface and Documentation Design | Oxford Academic. 'Frozen' princessANNA. We make a thorough ablation study to investigate the functionality of each component. In addition, the combination of lexical and syntactical conditions shows the significant controllable ability of paraphrase generation, and these empirical results could provide novel insight to user-oriented paraphrasing.
Most work targeting multilinguality, for example, considers only accuracy; most work on fairness or interpretability considers only English; and so on. Exaggerate intonation and stress. By the latter we mean spurious correlations between inputs and outputs that do not represent a generally held causal relationship between features and classes; models that exploit such correlations may appear to perform a given task well, but fail on out of sample data. Frazer, James George. Learned Incremental Representations for Parsing. 21 on BEA-2019 (test). HOLM: Hallucinating Objects with Language Models for Referring Expression Recognition in Partially-Observed Scenes. Moreover, we demonstrate that only Vrank shows human-like behavior in its strong ability to find better stories when the quality gap between two stories is high. Attention Temperature Matters in Abstractive Summarization Distillation. However, many existing Question Generation (QG) systems focus on generating extractive questions from the text, and have no way to control the type of the generated question. During that time, many people left the area because of persistent and sustained winds which disrupted their topsoil and consequently the desirability of their land.
Improved Multi-label Classification under Temporal Concept Drift: Rethinking Group-Robust Algorithms in a Label-Wise Setting. In relation to biblically-based assumptions that people have about when the earliest biblical events like the Tower of Babel and the great flood are likely to have happened, it is probably common to work with a time frame that involves thousands of years rather than tens of thousands of years. We perform an empirical study on a truly unsupervised version of the paradigm completion task and show that, while existing state-of-the-art models bridged by two newly proposed models we devise perform reasonably, there is still much room for improvement. The ambiguities in the questions enable automatically constructing true and false claims that reflect user confusions (e. g., the year of the movie being filmed vs. being released). 2) We apply the anomaly detector to a defense framework to enhance the robustness of PrLMs. To perform well on a machine reading comprehension (MRC) task, machine readers usually require commonsense knowledge that is not explicitly mentioned in the given documents. We conduct the experiments on two commonly-used datasets, and demonstrate the superior performance of PGKPR over comparative models on multiple evaluation metrics. Solving these requires models to ground linguistic phenomena in the visual modality, allowing more fine-grained evaluations than hitherto possible. Leveraging User Sentiment for Automatic Dialog Evaluation. Then we systematically compare these different strategies across multiple tasks and domains. We release an evaluation scheme and dataset for measuring the ability of NMT models to translate gender morphology correctly in unambiguous contexts across syntactically diverse sentences. To fully leverage the information of these different sets of labels, we propose NLSSum (Neural Label Search for Summarization), which jointly learns hierarchical weights for these different sets of labels together with our summarization model. Recently, the NLP community has witnessed a rapid advancement in multilingual and cross-lingual transfer research where the supervision is transferred from high-resource languages (HRLs) to low-resource languages (LRLs). This nature brings challenges to introducing commonsense in general text understanding tasks.
Experiments on summarization (CNN/DailyMail and XSum) and question generation (SQuAD), using existing and newly proposed automaticmetrics together with human-based evaluation, demonstrate that Composition Sampling is currently the best available decoding strategy for generating diverse meaningful outputs. We conclude with recommendations for model producers and consumers, and release models and replication code to accompany this paper. Active learning is the iterative construction of a classification model through targeted labeling, enabling significant labeling cost savings. The composition of richly-inflected words in morphologically complex languages can be a challenge for language learners developing literacy. Task-specific masks are obtained from annotated data in a source language, and language-specific masks from masked language modeling in a target language. In this work, we propose Mix and Match LM, a global score-based alternative for controllable text generation that combines arbitrary pre-trained black-box models for achieving the desired attributes in the generated text without involving any fine-tuning or structural assumptions about the black-box models. Gerasimos Lampouras. Neural machine translation (NMT) has obtained significant performance improvement over the recent years. Put through a sieve.
233 b Use figurative language to sway opinion, view life, and surprise the reader. With the coordinating conjunctions but and and clearly. Gooey treat spelled with an apostrophes. Bine ideas that are not often associated with each other. Ambiguous word with. Objective case, direct object Objective case, subject Pronoun as appositive. This two-word alliteration calls attention to the phrase and fixes it in the reader's mind, and so is useful for emphasis as well as art. Visitors in the million visit.
Takes the form of an opinion paper, an autobiographical reminiscence, or a personal, introspective essay. Just get to the point. It cannot correct improper usage of correctly spelled words {except for accept or altar for alter), and it does not contain a complete If. Separated from the preposition. The first place, iinfortimately, certainly, and other. Airports 10. or a corn field in Iowa. Specific ships, aircraft, name. 536. inside address, 535, insist, 49-50. Gooey treat spelled with apostrophe crossword. in regards to, 417 182-83, 228 intensive pronoim, 247 interjections, 20h: 256 institutions, {so, such, too), with, 36j: interrogative pronoun, 247. interview in citations, 295. indention AP. Direct objects, retained objects, indirect objects, complements 262 d Predicate nouns and predicate e Sentence constructions 264 f Sentence patterns 266. Maintain a consistent point of view? Most professionals keep a journal. MLA, resume.. "339 pronoun, 247.
Phrases and clauses. One's general safety on campus after dark can be secured by one's walking always with one's. This paper needed more work. Editing for tense and tense sequence, however, requires more than a. knowledge of simple present and simple. Argue a point of view. Wait for in the sense of "remain. Ferent meanings, different uses, and, especially, different spellings. Information the banker must provide before you sign the contract includes three items: (1) a clearly stated interest rate, (2) the total monthly payment, and (3) the number of payments due. They are not within an-. I also wish to thank draft, several students. 466. bibliographv cards, working, 50d: 471-74: 50e: 474-82. Strong, active verbs. When to use an apostrophe with a name. Italicize articles {a, an, the). Emojilock / to file.
A jack-o'-lantern, of course, our front yard for Halloween. Pleased that she smelled bad. Sp EXCEPTIONS: shortened words {memos [memorandums], antos [automobiles], pro5 [professionals]) and plural words that use either spelling {zeros and zeroes, mottos and mottoes, and nos and noes). Emphasis sparingly and only for good reason. A'., o^V, summary, 476. one, avoiding use of, note-taking avoiding plagiarism in, 50f: 480-82 for a purpose, 478 in research, 18-19, 50e: 474-80. noun clause, 275 noun phrase, 28, 260, 268-69 noun(s), 20a: 244-45 abstract, 245, figures, 44a: 410; 44b: spelling, 34n:. To avoid misspellings in your work, keep a dictionary handy and use it often. That are correct with. In the next example, editing maintains the consistency of. Generate ideas, even if you cannot answer 'journalist's questions" (Who? English, nonstandard. Three brothers Ted received his orders this week.