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Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing ...
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An Information-Theoretic Characterization of Morphological Fusion ...
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One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets ...
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Learning Data Augmentation Schedules for Natural Language Processing ...
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Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model ...
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A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders ...
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InFillmore: Frame-Guided Language Generation with Bidirectional Context ...
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Learning Embeddings for Rare Words Leveraging Internet Search Engine and Spatial Location Relationships ...
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Evaluating Universal Dependency Parser Recovery of Predicate Argument Structure via CompChain Analysis ...
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ParsFEVER : a Dataset for Farsi Fact Extraction and Verification ...
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Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge ...
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Teach the Rules, Provide the Facts: Targeted Relational-knowledge Enhancement for Textual Inference ...
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Abstract:
We present InferBert, a method to enhance transformer-based inference models with relevant relational knowledge. Our approach facilitates learning generic inference patterns requiring relational knowledge (e.g. inferences related to hypernymy) during training, while injecting on-demand the relevant relational facts (e.g. pangolin is an animal) at test time. We apply InferBERT to the NLI task over a diverse set of inference types (hypernymy, location, color, and country of origin), for which we collected challenge datasets. In this setting, InferBert succeeds to learn general inference patterns, from a relatively small number of training instances, while not hurting performance on the original NLI data and substantially outperforming prior knowledge enhancement models on the challenge data. It further applies its inferences successfully at test time to previously unobserved entities. InferBert is computationally more efficient than most prior methods, in terms of number of parameters, memory consumption and ...
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Keyword:
Computational Linguistics; Data Management System; FOS Languages and literature; Linguistics; Natural Language Processing; Semantics
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URL: https://dx.doi.org/10.48448/05ak-j010 https://underline.io/lecture/29793-teach-the-rules,-provide-the-facts-targeted-relational-knowledge-enhancement-for-textual-inference
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Exploring Pre-Trained Transformers and Bilingual Transfer Learning for Arabic Coreference Resolution ...
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Evaluating the Morphosyntactic Well-formedness of Generated Texts ...
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I Wish I Would Have Loved This One, But I Didn't -- A Multilingual Dataset for Counterfactual Detection in Product Review ...
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MultiEURLEX - A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer ...
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IR like a SIR: Sense-enhanced Information Retrieval for Multiple Languages ...
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