Papers with internal architecture

2 papers
Syntax-guided Neural Module Distillation to Probe Compositionality in Sentence Embeddings (2023.eacl-main)

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Challenge: Past work on sentence embedding models faces issues determining the causal impact of implicit syntax representations.
Approach: They construct a neural module net based on a transformer model and train it end-to-end to approximate the sentence’s embedding.
Outcome: The proposed model captures whether syntax is a strong model of its compositional ability.
FaiMA: Feature-aware In-context Learning for Multi-domain Aspect-based Sentiment Analysis (2024.lrec-main)

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Challenge: Existing methods for aspect-based sentiment analysis are limited and integrating with existing techniques is difficult.
Approach: They propose a framework that utilizes in-context learning as a feature-aware mechanism that facilitates adaptive learning in multi-domain ABSA tasks.
Outcome: The proposed framework achieves significant performance improvements in multiple domains compared to baselines, increasing F1 by 2.07% on average.

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