Papers Lexical Entailment
“Lexical Entailment” 태그가 달린 논문 45편 · 필터 해제
Emergent Visual-Semantic Hierarchies in Image-Text Representations
While recent vision-and-language models (VLMs) like CLIP are a powerful tool for analyzing text and images in a shared semantic space, they do not explicitly model the hierarchical nature of the set of texts which may de…
Hierarchical Text-Image MatchingLexical EntailmentRepresentation LearningTalking the Talk Does Not Entail Walking the Walk: On the Limits of Large Language Models in Lexical Entailment Recognition
Verbs form the backbone of language, providing the structure and meaning to sentences. Yet, their intricate semantic nuances pose a longstanding challenge. Understanding verb relations through the concept of lexical enta…
Lexical EntailmentSentenceTaxoLLaMA: WordNet-based Model for Solving Multiple Lexical Semantic Tasks
In this paper, we explore the capabilities of LLMs in capturing lexical-semantic knowledge from WordNet on the example of the LLaMA-2-7b model and test it on multiple lexical semantic tasks. As the outcome of our experim…
Domain AdaptationFew-Shot LearningHypernym DiscoveryLexical Entailment+1Testing Large Language Models on Compositionality and Inference with Phrase-Level Adjective-Noun Entailment
Previous work has demonstrated that pre-trained large language models (LLM) acquire knowledge during pre-training which enables reasoning over relationships between words (e.g, hyponymy) and more complex inferences over …
Lexical EntailmentTransfer LearningContinuous Entailment Patterns for Lexical Inference in Context
Combining a pretrained language model (PLM) with textual patterns has been shown to help in both zero- and few-shot settings. For zero-shot performance, it makes sense to design patterns that closely resemble the text se…
Few-Shot NLILanguage ModelingLexical EntailmentNatural Language UnderstandingSemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment
Lexical entailment (LE) is a fundamental asymmetric lexico-semantic relation, supporting the hierarchies in lexical resources (e.g., WordNet, ConceptNet) and applications like natural language inference and taxonomy indu…
Lexical EntailmentNatural Language InferenceTask 2BMEAUT at SemEval-2020 Task 2: Lexical Entailment with Semantic Graphs
In this paper we present a novel rule-based, language independent method for determining lexical entailment relations using semantic representations built from Wiktionary definitions. Combined with a simple WordNet-based…
Lexical EntailmentSemantic ParsingTask 2SHIKEBLCU at SemEval-2020 Task 2: An External Knowledge-enhanced Matrix for Multilingual and Cross-Lingual Lexical Entailment
Lexical entailment recognition plays an important role in tasks like Question Answering and Machine Translation. As important branches of lexical entailment, predicting multilingual and cross-lingual lexical entailment (…
Lexical EntailmentMachine TranslationMultilingual Word EmbeddingsQuestion Answering+3UAlberta at SemEval-2020 Task 2: Using Translations to Predict Cross-Lingual Entailment
We investigate the hypothesis that translations can be used to identify cross-lingual lexical entailment. We propose novel methods that leverage parallel corpora, word embeddings, and multilingual lexical resources. Our …
Lexical EntailmentTask 2Word EmbeddingsA Retrofitting Model for Incorporating Semantic Relations into Word Embeddings
We present a novel retrofitting model that can leverage relational knowledge available in a knowledge resource to improve word embeddings. The knowledge is captured in terms of relation inequality constraints that compar…
Lexical EntailmentMetric LearningTripletWord Embeddings+1Visual Objects As Context: Exploiting Visual Objects for Lexical Entailment
We propose a new word representation method derived from visual objects in associated images to tackle the lexical entailment task. Although it has been shown that the \textit{Distributional Informativeness Hypothesis} (…
InformativenessLexical EntailmentRussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark
In this paper, we introduce an advanced Russian general language understanding evaluation benchmark -- RussianGLUE. Recent advances in the field of universal language models and transformers require the development of a …
Common Sense ReasoningDiagnosticLexical EntailmentLogical Reasoning Question Answering+5Mining Knowledge for Natural Language Inference from Wikipedia Categories
Accurate lexical entailment (LE) and natural language inference (NLI) often require large quantities of costly annotations. To alleviate the need for labeled data, we introduce WikiNLI: a resource for improving model per…
Lexical EntailmentNatural Language InferenceHypernymy Detection for Low-Resource Languages via Meta Learning
Hypernymy detection, a.k.a, lexical entailment, is a fundamental sub-task of many natural language understanding tasks. Previous explorations mostly focus on monolingual hypernymy detection on high-resource languages, e.…
Lexical EntailmentMeta-LearningNatural Language UnderstandingWord Attribute Prediction Enhanced by Lexical Entailment Tasks
Human semantic knowledge about concepts acquired through perceptual inputs and daily experiences can be expressed as a bundle of attributes. Unlike the conventional distributed word representations that are purely induce…
AttributeLexical EntailmentPredictionvalidNeural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation
We address whether neural models for Natural Language Inference (NLI) can learn the compositional interactions between lexical entailment and negation, using four methods: the behavioral evaluation methods of (1) challen…
Lexical EntailmentNatural Language InferenceNegationSystematic GeneralizationTextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP
While there has been substantial research using adversarial attacks to analyze NLP models, each attack is implemented in its own code repository. It remains challenging to develop NLP attacks and utilize them to improve …
Adversarial AttackAdversarial TextData AugmentationLexical Entailment+2Discriminative Topic Mining via Category-Name Guided Text Embedding
Mining a set of meaningful and distinctive topics automatically from massive text corpora has broad applications. Existing topic models, however, typically work in a purely unsupervised way, which often generate topics t…
Document ClassificationGeneral ClassificationLexical EntailmentTopic Models+1Specializing Distributional Vectors of All Words for Lexical Entailment
Semantic specialization methods fine-tune distributional word vectors using lexical knowledge from external resources (e.g. WordNet) to accentuate a particular relation between words. However, such post-processing method…
AllCross-Lingual TransferLexical EntailmentRelation+2Generalized Tuning of Distributional Word Vectors for Monolingual and Cross-Lingual Lexical Entailment
Lexical entailment (LE; also known as hyponymy-hypernymy or is-a relation) is a core asymmetric lexical relation that supports tasks like taxonomy induction and text generation. In this work, we propose a simple and effe…
Lexical EntailmentRelationText Generation