Papers with language model embeddings
Locally Aggregated Feature Attribution on Natural Language Model Understanding (2022.naacl-main)
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| Challenge: | a growing popularity of deep-learning models makes model understanding more important . feature attribution methods have shown promising results in computer vision but are not trivial . |
| Approach: | They propose a gradient-based feature attribution method that smooths gradients by aggregating similar reference texts derived from language model embeddings. |
| Outcome: | The proposed method outperforms existing methods on public datasets and key words detection tasks. |
Mapping the Circumplex of Affect: Geometric Analysis of Emotion Representations via Hyperspherical Contrastive Learning (2026.acl-long)
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| Challenge: | Existing methods to induce circular emotion representations in language models are limited . elucidates trade-offs involved in applying circumplex models to deep learning architectures . |
| Approach: | They propose a method to induce circular emotion representations within language models via contrastive learning on a hypersphere. |
| Outcome: | The proposed method underperforms in high-dimensional settings and fine-grained classification. |
Towards Few-shot Entity Recognition in Document Images: A Graph Neural Network Approach Robust to Image Manipulation (2024.lrec-main)
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| Challenge: | Existing methods for named entity recognition from document images are limited in few-shot settings. |
| Approach: | They propose a framework which leverages the topological adjacency relationship among tokens by learning layout information with graph neural networks. |
| Outcome: | The proposed framework outperforms baselines under different few-shot settings and shows better performance to image manipulations. |