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Negation

Papers

Showing 376400 of 608 papers

TitleStatusHype
System of Spheres-based Two Level Credibility-limited Revisions0
TAG: Toward Accurate Social Media Content Tagging with a Concept Graph0
TDCGL: Two-Level Debiased Contrastive Graph Learning for Recommendation0
Text-driven 3D Human Generation via Contrastive Preference Optimization0
The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes0
The Case of Imperfect Negation Cues: A Two-Step Approach for Automatic Negation Scope Resolution0
The First Shared Task on Discourse Representation Structure Parsing0
The lexical and grammatical sources of neg-raising inferences0
The Lindstrom's Characterizability of Abstract Logic Systems for Analytic Structures Based on Measures0
The negation of permutation mass function0
There Is No Logical Negation Here, But There Are Alternatives: Modeling Conversational Negation with Distributional Semantics0
The Scope and Focus of Negation: A Complete Annotation Framework for Italian0
The Self-Contained Negation Test Set0
The University of Arizona at SemEval-2021 Task 10: Applying Self-training, Active Learning and Data Augmentation to Source-free Domain Adaptation0
Three Kinds of Negation in Knowledge and Their Mathematical Foundations0
Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understanding0
TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP0
Top-Down Knowledge Compilation for Counting Modulo Theories0
Topological and Algebraic Structures of Atanassov's Intuitionistic Fuzzy-Values Space0
To Schedule or not to Schedule: Extracting Task Specific Temporal Entities and Associated Negation Constraints0
Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features0
Towards logical negation for compositional distributional semantics0
Towards Proof Synthesis Guided by Neural Machine Translation for Intuitionistic Propositional Logic0
Towards Understanding and Answering Multi-Sentence Recommendation Questions on Tourism0
Training-Free Safe Denoisers for Safe Use of Diffusion Models0
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