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SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing. To address these challenges, we propose a novel Learn to Adapt (LTA) network using a variant meta-learning framework. Targeted readers may also have different backgrounds and educational levels. Experiments show that the proposed method significantly outperforms strong baselines on multiple MMT datasets, especially when the textual context is limited. In an educated manner wsj crossword puzzle crosswords. BiTIIMT: A Bilingual Text-infilling Method for Interactive Machine Translation. In argumentation technology, however, this is barely exploited so far. CQG employs a simple method to generate the multi-hop questions that contain key entities in multi-hop reasoning chains, which ensure the complexity and quality of the questions.

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Meanwhile, SS-AGA features a new pair generator that dynamically captures potential alignment pairs in a self-supervised paradigm. They exhibit substantially lower computation complexity and are better suited to symmetric tasks. We formulate a generative model of action sequences in which goals generate sequences of high-level subtask descriptions, and these descriptions generate sequences of low-level actions. Detecting it is an important and challenging problem to prevent large scale misinformation and maintain a healthy society. Our model encourages language-agnostic encodings by jointly optimizing for logical-form generation with auxiliary objectives designed for cross-lingual latent representation alignment. We then design a harder self-supervision objective by increasing the ratio of negative samples within a contrastive learning setup, and enhance the model further through automatic hard negative mining coupled with a large global negative queue encoded by a momentum encoder. In an educated manner wsj crossword key. Attention has been seen as a solution to increase performance, while providing some explanations. We present Tailor, a semantically-controlled text generation system. 4) Our experiments on the multi-speaker dataset lead to similar conclusions as above and providing more variance information can reduce the difficulty of modeling the target data distribution and alleviate the requirements for model capacity.

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Knowledge probing is crucial for understanding the knowledge transfer mechanism behind the pre-trained language models (PLMs). In this paper, we review contemporary studies in the emerging field of VLN, covering tasks, evaluation metrics, methods, etc. Efficient Hyper-parameter Search for Knowledge Graph Embedding. In an educated manner crossword clue. Fourth, we compare different pretraining strategies and for the first time establish that pretraining is effective for sign language recognition by demonstrating (a) improved fine-tuning performance especially in low-resource settings, and (b) high crosslingual transfer from Indian-SL to few other sign languages. Summarizing biomedical discovery from genomics data using natural languages is an essential step in biomedical research but is mostly done manually. AraT5: Text-to-Text Transformers for Arabic Language Generation.

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The generated commonsense augments effective self-supervision to facilitate both high-quality negative sampling (NS) and joint commonsense and fact-view link prediction. Topics covered include literature, philosophy, history, science, the social sciences, music, art, drama, archaeology and architecture. To test compositional generalization in semantic parsing, Keysers et al. This framework can efficiently rank chatbots independently from their model architectures and the domains for which they are trained. We collect non-toxic paraphrases for over 10, 000 English toxic sentences. Leveraging large-scale unlabeled speech and text data, we pre-train SpeechT5 to learn a unified-modal representation, hoping to improve the modeling capability for both speech and text. "He was a mysterious character, closed and introverted, " Zaki Mohamed Zaki, a Cairo journalist who was a classmate of his, told me. His brother was a highly regarded dermatologist and an expert on venereal diseases. Empirical results suggest that our method vastly outperforms two baselines in both accuracy and F1 scores and has a strong correlation with human judgments on factuality classification tasks. In an educated manner wsj crossword november. Code and model are publicly available at Dependency-based Mixture Language Models. Richard Yuanzhe Pang. On the other hand, logic-based approaches provide interpretable rules to infer the target answer, but mostly work on structured data where entities and relations are well-defined. We conduct extensive experiments and show that our CeMAT can achieve significant performance improvement for all scenarios from low- to extremely high-resource languages, i. e., up to +14. Our approach first extracts a set of features combining human intuition about the task with model attributions generated by black box interpretation techniques, then uses a simple calibrator, in the form of a classifier, to predict whether the base model was correct or not.

First, we design a two-step approach: extractive summarization followed by abstractive summarization. NP2IO leverages pretrained language modeling to classify Insiders and Outsiders. FairLex: A Multilingual Benchmark for Evaluating Fairness in Legal Text Processing. Rex Parker Does the NYT Crossword Puzzle: February 2020. EGT2 learns the local entailment relations by recognizing the textual entailment between template sentences formed by typed CCG-parsed predicates.

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