Papers with compositional model

3 papers
LexSym: Compositionality as Lexical Symmetry (2023.acl-long)

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Challenge: Existing approaches to generalize compositional models fail to generalise from small datasets.
Approach: They propose a domain-general and model-agnostic formulation of compositionality as a constraint on symmetries of data distributions rather than models.
Outcome: The proposed procedure matches or surpasses state-of-the-art, task-specific models on COGS semantic parsing, SCAN and Alchemy instruction following, and CLEVR-CoGenT visual question answering datasets.
Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs (D18-1)

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Challenge: a paper addresses the problem of mapping natural language text to knowledge base entities.
Approach: They propose a model for mapping natural language text to knowledge base entities using a multi-dimensional entity space obtained from a knowledge graph.
Outcome: The proposed model is applied to large-scale text-to-entity mapping and entity classification tasks with state-of-the-art results.
Multi-Step Inference for Reasoning Over Paragraphs (2020.emnlp-main)

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Challenge: Existing models for complex reasoning use symbols or black-box transformers . a compositional model can chain together free-form predicates and logical connectives .
Approach: They propose a compositional model that finds relevant sentences and then chains them together using neural modules.
Outcome: The proposed model improves performance on a recently-introduced dataset.

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