Comic Book Culture, News, Humor And Commentary, Rex Parker Does The Nyt Crossword Puzzle: February 2020

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Specifically, given the streaming inputs, we first predict the full-sentence length and then fill the future source position with positional encoding, thereby turning the streaming inputs into a pseudo full-sentence. The EPT-X model yields an average baseline performance of 69. While prior work has proposed models that improve faithfulness, it is unclear whether the improvement comes from an increased level of extractiveness of the model outputs as one naive way to improve faithfulness is to make summarization models more extractive. We demonstrate the effectiveness of these perturbations in multiple applications. Research in stance detection has so far focused on models which leverage purely textual input. Moreover, in experiments on TIMIT and Mboshi benchmarks, our approach consistently learns a better phoneme-level representation and achieves a lower error rate in a zero-resource phoneme recognition task than previous state-of-the-art self-supervised representation learning algorithms. Higher-order methods for dependency parsing can partially but not fully address the issue that edges in dependency trees should be constructed at the text span/subtree level rather than word level. In an educated manner wsj crossword december. Each man filled a need in the other. UCTopic outperforms the state-of-the-art phrase representation model by 38. ChatMatch: Evaluating Chatbots by Autonomous Chat Tournaments. To assess the impact of methodologies, we collect a dataset of (code, comment) pairs with timestamps to train and evaluate several recent ML models for code summarization. A given base model will then be trained via the constructed data curricula, i. first on augmented distilled samples and then on original ones. The ability to sequence unordered events is evidence of comprehension and reasoning about real world tasks/procedures.

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We reduce the gap between zero-shot baselines from prior work and supervised models by as much as 29% on RefCOCOg, and on RefGTA (video game imagery), ReCLIP's relative improvement over supervised ReC models trained on real images is 8%. While significant progress has been made on the task of Legal Judgment Prediction (LJP) in recent years, the incorrect predictions made by SOTA LJP models can be attributed in part to their failure to (1) locate the key event information that determines the judgment, and (2) exploit the cross-task consistency constraints that exist among the subtasks of LJP. To address this gap, we systematically analyze the robustness of state-of-the-art offensive language classifiers against more crafty adversarial attacks that leverage greedy- and attention-based word selection and context-aware embeddings for word replacement. This paper discusses the adaptability problem in existing OIE systems and designs a new adaptable and efficient OIE system - OIE@OIA as a solution. In contrast to existing OIE benchmarks, BenchIE is fact-based, i. In an educated manner wsj crossword game. e., it takes into account informational equivalence of extractions: our gold standard consists of fact synsets, clusters in which we exhaustively list all acceptable surface forms of the same fact. Long-range semantic coherence remains a challenge in automatic language generation and understanding. TwittIrish: A Universal Dependencies Treebank of Tweets in Modern Irish.

Furthermore, we propose a latent-mapping algorithm in the latent space to convert the amateur vocal tone to the professional one. We consider text-to-table as an inverse problem of the well-studied table-to-text, and make use of four existing table-to-text datasets in our experiments on text-to-table. Furthermore, we devise a cross-modal graph convolutional network to make sense of the incongruity relations between modalities for multi-modal sarcasm detection. And yet, the dependencies these formalisms share with respect to language-specific repositories of knowledge make the objective of closing the gap between high- and low-resourced languages hard to accomplish. Our experiments show that HOLM performs better than the state-of-the-art approaches on two datasets for dRER; allowing to study generalization for both indoor and outdoor settings. First, we design a two-step approach: extractive summarization followed by abstractive summarization. We conduct experiments on two text classification datasets – Jigsaw Toxicity, and Bias in Bios, and evaluate the correlations between metrics and manual annotations on whether the model produced a fair outcome. ReCLIP: A Strong Zero-Shot Baseline for Referring Expression Comprehension. We empirically evaluate different transformer-based models injected with linguistic information in (a) binary bragging classification, i. e., if tweets contain bragging statements or not; and (b) multi-class bragging type prediction including not bragging. Formality style transfer (FST) is a task that involves paraphrasing an informal sentence into a formal one without altering its meaning. Rex Parker Does the NYT Crossword Puzzle: February 2020. We conduct experiments on both synthetic and real-world datasets. An Empirical Study of Memorization in NLP.

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Paraphrases can be generated by decoding back to the source from this representation, without having to generate pivot translations. Retrieval-based methods have been shown to be effective in NLP tasks via introducing external knowledge. Jonathan K. Kummerfeld. Animals and Pets Anime Art Cars and Motor Vehicles Crafts and DIY Culture, Race, and Ethnicity Ethics and Philosophy Fashion Food and Drink History Hobbies Law Learning and Education Military Movies Music Place Podcasts and Streamers Politics Programming Reading, Writing, and Literature Religion and Spirituality Science Tabletop Games Technology Travel. Although the Chinese language has a long history, previous Chinese natural language processing research has primarily focused on tasks within a specific era. Molecular representation learning plays an essential role in cheminformatics. A well-calibrated neural model produces confidence (probability outputs) closely approximated by the expected accuracy. In an educated manner crossword clue. In this paper, we introduce HOLM, Hallucinating Objects with Language Models, to address the challenge of partial observability. On the one hand, AdSPT adopts separate soft prompts instead of hard templates to learn different vectors for different domains, thus alleviating the domain discrepancy of the \operatorname{[MASK]} token in the masked language modeling task. In addition, a thorough analysis of the prototype-based clustering method demonstrates that the learned prototype vectors are able to implicitly capture various relations between events.

An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor Isomorphism. Our work demonstrates the feasibility and importance of pragmatic inferences on news headlines to help enhance AI-guided misinformation detection and mitigation. In addition, we introduce a novel controlled Transformer-based decoder to guarantee that key entities appear in the questions. JoVE Core BiologyThis link opens in a new windowKings username and password for access off campus. For one thing, both were very much modern men. A Well-Composed Text is Half Done! In an educated manner wsj crossword puzzle answers. Low-Rank Softmax Can Have Unargmaxable Classes in Theory but Rarely in Practice. Multimodal machine translation and textual chat translation have received considerable attention in recent years. Transfer learning with a unified Transformer framework (T5) that converts all language problems into a text-to-text format was recently proposed as a simple and effective transfer learning approach. In this study, we crowdsource multiple-choice reading comprehension questions for passages taken from seven qualitatively distinct sources, analyzing what attributes of passages contribute to the difficulty and question types of the collected examples.

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Recent work has explored using counterfactually-augmented data (CAD)—data generated by minimally perturbing examples to flip the ground-truth label—to identify robust features that are invariant under distribution shift. Rixie Tiffany Leong. Experiment results on various sequences of generation tasks show that our framework can adaptively add modules or reuse modules based on task similarity, outperforming state-of-the-art baselines in terms of both performance and parameter efficiency. We therefore propose Label Semantic Aware Pre-training (LSAP) to improve the generalization and data efficiency of text classification systems. Analytical results verify that our confidence estimate can correctly assess underlying risk in two real-world scenarios: (1) discovering noisy samples and (2) detecting out-of-domain data. Moreover, we find that these two methods can further be combined with the backdoor attack to misguide the FMS to select poisoned models. Large language models, even though they store an impressive amount of knowledge within their weights, are known to hallucinate facts when generating dialogue (Shuster et al., 2021); moreover, those facts are frozen in time at the point of model training. " Road 9 runs beside train tracks that separate the tony side of Maadi from the baladi district—the native part of town. Learning representations of words in a continuous space is perhaps the most fundamental task in NLP, however words interact in ways much richer than vector dot product similarity can provide. With the availability of this dataset, our hope is that the NMT community can iterate on solutions for this class of especially egregious errors. Furthermore, we develop an attribution method to better understand why a training instance is memorized.

Based on these insights, we design an alternative similarity metric that mitigates this issue by requiring the entire translation distribution to match, and implement a relaxation of it through the Information Bottleneck method. In this paper we explore the design space of Transformer models showing that the inductive biases given to the model by several design decisions significantly impact compositional generalization. Semi-Supervised Formality Style Transfer with Consistency Training. 83 ROUGE-1), reaching a new state-of-the-art. Code and datasets are available at: Substructure Distribution Projection for Zero-Shot Cross-Lingual Dependency Parsing. When primed with only a handful of training samples, very large, pretrained language models such as GPT-3 have shown competitive results when compared to fully-supervised, fine-tuned, large, pretrained language models. Hyde e. g. crossword clue. South Asia is home to a plethora of languages, many of which severely lack access to new language technologies.

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