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Experiments demonstrate that LAGr achieves significant improvements in systematic generalization upon the baseline seq2seq parsers in both strongly- and weakly-supervised settings. We conducted extensive experiments on six text classification datasets and found that with sixteen labeled examples, EICO achieves competitive performance compared to existing self-training few-shot learning methods. Our insistence on meaning preservation makes positive reframing a challenging and semantically rich task.

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In this paper, we first identify the cause of the failure of the deep decoder in the Transformer model. Through experiments on the Levy-Holt dataset, we verify the strength of our Chinese entailment graph, and reveal the cross-lingual complementarity: on the parallel Levy-Holt dataset, an ensemble of Chinese and English entailment graphs outperforms both monolingual graphs, and raises unsupervised SOTA by 4. Julia Rivard Dexter. Natural language processing (NLP) systems have become a central technology in communication, education, medicine, artificial intelligence, and many other domains of research and development. Moreover, we impose a new regularization term into the classification objective to enforce the monotonic change of approval prediction w. r. t. Newsday Crossword February 20 2022 Answers –. novelty scores. We demonstrate that instance-level is better able to distinguish between different domains compared to corpus-level frameworks proposed in previous studies Finally, we perform in-depth analyses of the results highlighting the limitations of our approach, and provide directions for future research. We separately release the clue-answer pairs from these puzzles as an open-domain question answering dataset containing over half a million unique clue-answer pairs. However, previous works have relied heavily on elaborate components for a specific language model, usually recurrent neural network (RNN), which makes themselves unwieldy in practice to fit into other neural language models, such as Transformer and GPT-2. We propose that a sound change can be captured by comparing the relative distance through time between the distributions of the characters involved before and after the change has taken place. Our approach significantly improves output quality on both tasks and controls output complexity better on the simplification task. TABi improves retrieval of rare entities on the Ambiguous Entity Retrieval (AmbER) sets, while maintaining strong overall retrieval performance on open-domain tasks in the KILT benchmark compared to state-of-the-art retrievers. Existing conversational QA benchmarks compare models with pre-collected human-human conversations, using ground-truth answers provided in conversational history. Attention mechanism has become the dominant module in natural language processing models.

Linguistic Term For A Misleading Cognate Crosswords

Models generated many false answers that mimic popular misconceptions and have the potential to deceive humans. Cluster & Tune: Boost Cold Start Performance in Text Classification. Besides formalizing the approach, this study reports simulations of human experiments with DIORA (Drozdov et al., 2020), a neural unsupervised constituency parser. Using Cognates to Develop Comprehension in English. Then we systematically compare these different strategies across multiple tasks and domains.

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Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifold. Leveraging these pseudo sequences, we are able to construct same-length positive and negative pairs based on the attention mechanism to perform contrastive learning. Linguistic term for a misleading cognate crossword puzzle crosswords. This strategy avoids search through the whole datastore for nearest neighbors and drastically improves decoding efficiency. Our results show that our models can predict bragging with macro F1 up to 72.

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Miscreants in movies. Finally, the practical evaluation toolkit is released for future benchmarking purposes. Through analyzing the connection between the program tree and the dependency tree, we define a unified concept, operation-oriented tree, to mine structure features, and introduce Structure-Aware Semantic Parsing to integrate structure features into program generation. To achieve this goal, this paper proposes a framework to automatically generate many dialogues without human involvement, in which any powerful open-domain dialogue generation model can be easily leveraged. 84% on average among 8 automatic evaluation metrics. We further explore the trade-off between available data for new users and how well their language can be modeled. 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. On a wide range of tasks across NLU, conditional and unconditional generation, GLM outperforms BERT, T5, and GPT given the same model sizes and data, and achieves the best performance from a single pretrained model with 1. Linguistic term for a misleading cognate crossword clue. Despite the remarkable success deep models have achieved in Textual Matching (TM) tasks, it still remains unclear whether they truly understand language or measure the semantic similarity of texts by exploiting statistical bias in datasets. By carefully designing experiments, we identify two representative characteristics of the data gap in source: (1) style gap (i. e., translated vs. natural text style) that leads to poor generalization capability; (2) content gap that induces the model to produce hallucination content biased towards the target language. Inspired by recent research in parameter-efficient transfer learning from pretrained models, this paper proposes a fusion-based generalisation method that learns to combine domain-specific parameters. In light of model diversity and the difficulty of model selection, we propose a unified framework, UniPELT, which incorporates different PELT methods as submodules and learns to activate the ones that best suit the current data or task setup via gating mechanism.

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The patient is more dead than alive: exploring the current state of the multi-document summarisation of the biomedical literature. In this paper, we propose LaPraDoR, a pretrained dual-tower dense retriever that does not require any supervised data for training. In this paper, we formulate this challenging yet practical problem as continual few-shot relation learning (CFRL). Without altering the training strategy, the task objective can be optimized on the selected subset. Folk-tales of Salishan and Sahaptin tribes.

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We propose fill-in-the-blanks as a video understanding evaluation framework and introduce FIBER – a novel dataset consisting of 28, 000 videos and descriptions in support of this evaluation framework. One of the reasons for this is a lack of content-focused elaborated feedback datasets. In this paper, we address the challenge by leveraging both lexical features and structure features for program generation. Further, we propose a new intrinsic evaluation method called EvalRank, which shows a much stronger correlation with downstream tasks. Roadway pavement warning. We hypothesize that enriching models with speaker information in a controlled, educated way can guide them to pick up on relevant inductive biases. In this work, we propose a novel transfer learning strategy to overcome these challenges. These methods have recently been applied to KG link prediction and question answering over incomplete KGs (KGQA). When directly using existing text generation datasets for controllable generation, we are facing the problem of not having the domain knowledge and thus the aspects that could be controlled are limited. Code and model are publicly available at Dependency-based Mixture Language Models. We therefore include a comparison of state-of-the-art models (i) with and without personas, to measure the contribution of personas to conversation quality, as well as (ii) prescribed versus freely chosen topics.

In essence, these classifiers represent community level language norms. Recent parameter-efficient language model tuning (PELT) methods manage to match the performance of fine-tuning with much fewer trainable parameters and perform especially well when training data is limited. S 2 SQL: Injecting Syntax to Question-Schema Interaction Graph Encoder for Text-to-SQL Parsers. Crowdsourcing is one practical solution for this problem, aiming to create a large-scale but quality-unguaranteed corpus. It is a common phenomenon in daily life, but little attention has been paid to it in previous work. However, the performance of text-based methods still largely lag behind graph embedding-based methods like TransE (Bordes et al., 2013) and RotatE (Sun et al., 2019b). Mohammad Javad Hosseini.

To address this issue, we propose a novel framework that unifies the document classifier with handcrafted features, particularly time-dependent novelty scores. Why Exposure Bias Matters: An Imitation Learning Perspective of Error Accumulation in Language Generation. However, a document can usually answer multiple potential queries from different views. Our work is the first step towards filling this gap: our goal is to develop robust classifiers to identify documents containing personal experiences and reports. By applying the proposed DoKTra framework to downstream tasks in the biomedical, clinical, and financial domains, our student models can retain a high percentage of teacher performance and even outperform the teachers in certain tasks. Principled Paraphrase Generation with Parallel Corpora.

Many tasks in text-based computational social science (CSS) involve the classification of political statements into categories based on a domain-specific codebook. This reduces the number of human annotations required further by 89%. Sheena Panthaplackel. We develop novel methods to generate 24k semiautomatic pairs as well as manually creating 1. Experiments on three benchmark datasets verify the efficacy of our method, especially on datasets where conflicts are severe. Graph Refinement for Coreference Resolution. In this paper, we propose a unified framework to learn the relational reasoning patterns for this task. All the code and data of this paper are available at Table-based Fact Verification with Self-adaptive Mixture of Experts. Fast and reliable evaluation metrics are key to R&D progress. By introducing an additional discriminative token and applying a data augmentation technique, valid paths can be automatically selected. EICO: Improving Few-Shot Text Classification via Explicit and Implicit Consistency Regularization. The experimental results on two challenging logical reasoning benchmarks, i. e., ReClor and LogiQA, demonstrate that our method outperforms the SOTA baselines with significant improvements. Neural machine translation (NMT) has obtained significant performance improvement over the recent years. Information extraction suffers from its varying targets, heterogeneous structures, and demand-specific schemas.

On standard evaluation benchmarks for knowledge-enhanced LMs, the method exceeds the base-LM baseline by an average of 4. Language models excel at generating coherent text, and model compression techniques such as knowledge distillation have enabled their use in resource-constrained settings. Modeling Syntactic-Semantic Dependency Correlations in Semantic Role Labeling Using Mixture Models. Thai Nested Named Entity Recognition Corpus. We hope this work fills the gap in the study of structured pruning on multilingual pre-trained models and sheds light on future research. Unfortunately, because the units used in GSLM discard most prosodic information, GSLM fails to leverage prosody for better comprehension and does not generate expressive speech. However, we find that different faithfulness metrics show conflicting preferences when comparing different interpretations. The reason why you are here is that you are looking for help regarding the Newsday Crossword puzzle. Time Expressions in Different Cultures. Can Transformer be Too Compositional? These paradigms, however, are not without flaws, i. e., running the model on all query-document pairs at inference-time incurs a significant computational cost.

Please help us keep this calendar up to date! Seeing it all come together was one of the highlights for performer, Brooke Loewen, Grade 7, who played Lumiere. Art and Drama students, and a number of enthusiastic helpers from the community, took the lead in designing, building and painting the impressive sets. Half Price Kids Ages 5-16**. Medieval and Renaissance Texts and Studies 569. Who will play the characters we have loved since childhood? Group rates available for ten or more. One student commented on what an amazing job everyone did, sharing that she has never seen a high school play quite like this one. From charming cottages, through creepy woods, to a forgotten, enchanted castle, this set is magnificent. "Jade Jones's superb performance raises Belle to a new level. The heartwarming tale of Belle and the Beast swirls to life in this lush stage performance. Step into the enchanted world of Broadway's modern classic, Disney's Beauty and the Beast, an international sensation that played a remarkable 13-year run on Broadway and was nominated for nine Tony Awards, including Best Musical. Beauty & The Beast The Musical at Patchogue Theatre - About. Whenever Disney announces plans to develop a live-action version of a cherished and classic animated film, there is bound to be skepticism and doubt. If you have a question about the activity itself, please contact the organization administrator listed below.

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Nonetheless, from the moment the first note crossed her lips, I was surprised and enchanted by her musical talent. Matthew DeFusco is a staff writer with Trib Total Media. The scene in the tavern where they celebrate Gaston with his namesake song is boisterous and hysterical, with his sidekick LeFou—played by Courtier Simmons—adding his own comedic genius to the number. Gabrielle-Suzanne Barbot de Villeneuve, the little-known author of Beauty and the Beast, was a successful novelist and fairytale writer in mid eighteenth-century France. MTI does not specifically approve, advocate or endorse any of the products or services listed. She was the brightest star onstage as the beloved beauty, lending her own distinctive sass and strength to the character. The Washington Post. Beauty and the Beast set rental package. Beauty & The Beast Jr. Gateway to stage production of 'Beauty and the Beast' next week. July 23 - August 6, 2022.

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The intricate set, which was drafted and painted by professional set designer Alfred Kirschman, includes several large pieces to portray the village Belle grew up in as well as the vast domain of the Beast. "It's hard, it's challenging and it's something that's really fun, too, once you get into it. Please be sure to click through directly to the organization's website to verify. Please note: MTI is not involved in the actual transaction between buyers and sellers. A friend and fellow Disney lover of mine said that she felt Watson's portrayal of Belle was inconsistent, especially concerning her accent. I dare you not to laugh out loud! The actors brought back everything I loved about the original story and shed new light on it. Gateway beauty and the breast cancer. There are currently no upcoming dates for Beauty and the Beast Production. She longs for something more than the life she has been given. If this activity is sold out, canceled, or otherwise needs alteration, email so we can update it immediately. Hager also portrayed Gaston in the National Tour of Beauty and the Beast and it's no wonder why The Gateway cast him—he's positively delightful as the villain everyone loves to hate. All of the students in the musical are volunteers who were interested in doing a musical.

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Let Disney Genie service summon the attractions, entertainment and dining you love most. Age Recommendation: Our children's shows are recommended for ages 3 and older. She brings a fresh and modern feel to the classic tale we all know and love.

Special Bonus: Helen Hayes Award-winner Tracy Lynn Olivera joins the Beauty cast as Madame de la Grande Bouche. Women's Writing (2021).