Lexical Entailment

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

6 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

18 shown of 18 papers with code (45 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark
  29 Oct 2020 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  In this paper, we introduce an advanced Russian general language understanding evaluation benchmark -- RussianGLUE.
• TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP
  29 Apr 2020 2 repositories listed
  TextAttack also includes data augmentation and adversarial training modules for using components of adversarial attacks to improve model accuracy and robustness.
• Hierarchical Density Order Embeddings
  26 Apr 2018 2 repositories listed
  By representing words with probability densities rather than point vectors, probabilistic word embeddings can capture rich and interpretable semantic information and uncertainty.
• Emergent Visual-Semantic Hierarchies in Image-Text Representations
  11 Jul 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  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…
• TaxoLLaMA: WordNet-based Model for Solving Multiple Lexical Semantic Tasks
  14 Mar 2024 1 repository listed
  It achieves 11 SotA results, 4 top-2 results out of 16 tasks for the Taxonomy Enrichment, Hypernym Discovery, Taxonomy Construction, and Lexical Entailment tasks.
• Testing Large Language Models on Compositionality and Inference with Phrase-Level Adjective-Noun Entailment
  1 Oct 2022 1 repository listed
  Here, we investigate whether lexical entailment (LE, i.
• Continuous Entailment Patterns for Lexical Inference in Context
  8 Sep 2021 1 repository listed
  If we allow for tokens outside the PLM's vocabulary, patterns can be adapted more flexibly to a PLM's idiosyncrasies.
• Mining Knowledge for Natural Language Inference from Wikipedia Categories
  3 Oct 2020 1 repository listed Syntology ran 0 of 2 samples · 2 unverified
  Accurate lexical entailment (LE) and natural language inference (NLI) often require large quantities of costly annotations.
• Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation
  30 Apr 2020 1 repository listed
  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)…
• Discriminative Topic Mining via Category-Name Guided Text Embedding
  20 Aug 2019 1 repository listed
  We propose a new task, discriminative topic mining, which leverages a set of user-provided category names to mine discriminative topics from text corpora.
• Generalized Tuning of Distributional Word Vectors for Monolingual and Cross-Lingual Lexical Entailment
  1 Jul 2019 1 repository listed
  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.
• SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference
  4 Jun 2019 1 repository listed
  We present SherLIiC, a testbed for lexical inference in context (LIiC), consisting of 3985 manually annotated inference rule candidates (InfCands), accompanied by (i) ~960k unlabeled InfCands, and (ii) ~190k typed…
• Specialising Word Vectors for Lexical Entailment
  1 Jun 2018 1 repository listed
  We present LEAR (Lexical Entailment Attract-Repel), a novel post-processing method that transforms any input word vector space to emphasise the asymmetric relation of lexical entailment (LE), also known as the IS-A or…
• Scoring Lexical Entailment with a Supervised Directional Similarity Network
  23 May 2018 1 repository listed
  Experiments show excellent performance on scoring graded lexical entailment, raising the state-of-the-art on the HyperLex dataset by approximately 25%.
• Specialising Word Vectors for Lexical Entailment
  17 Oct 2017 1 repository listed
  We present LEAR (Lexical Entailment Attract-Repel), a novel post-processing method that transforms any input word vector space to emphasise the asymmetric relation of lexical entailment (LE), also known as the IS-A or…
• A Consolidated Open Knowledge Representation for Multiple Texts
  1 Apr 2017 1 repository listed
  We propose to move from Open Information Extraction (OIE) ahead to Open Knowledge Representation (OKR), aiming to represent information conveyed jointly in a set of texts in an open text-based manner.
• Representing Meaning with a Combination of Logical and Distributional Models
  26 May 2015 1 repository listed
  In this paper, we focus on the three components of a practical system integrating logical and distributional models: 1) Parsing and task representation is the logic-based part where input problems are represented in…
• Experiments with Three Approaches to Recognizing Lexical Entailment
  31 Jan 2014 1 repository listed
  Two general strategies for RLE have been proposed: One strategy is to manually construct an asymmetric similarity measure for context vectors (directional similarity) and another is to treat RLE as a problem of learning…

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.