Papers with SAL
Gold Doesn’t Always Glitter: Spectral Removal of Linear and Nonlinear Guarded Attribute Information (2023.eacl-main)
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| Challenge: | Spectral Attribute removaL is a method to remove private or guarded information from neural representations. |
| Approach: | They propose a method to remove guarded or private information from neural representations by matrix decomposition. |
| Outcome: | The proposed method retains better main task performance after removing guarded information compared to previous work. |
Inducing Systematicity in Transformers by Attending to Structurally Quantized Embeddings (2024.acl-long)
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| Challenge: | Empirically, we show SQ-Transformer achieves stronger compositional generalization than the vanilla Transformer on low-complexity datasets. |
| Approach: | They propose a Transformer that explicitly encourages systematicity in the embeddings and attention layers even with low-complexity data. |
| Outcome: | Empirically, the proposed model achieves stronger compositional generalization than the vanilla Transformer on low-complexity datasets. |
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning (D19-1)
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| Challenge: | Existing methods to extract aspects and sentiments are limited due to lack of annotated sequence data. |
| Approach: | They propose a Selective Adversarial Learning method to align latent correlation vectors . they propose tagging a set of aspect boundary tags and sentiment tags to create a joint label space . |
| Outcome: | The proposed method can learn weights for words to achieve fine-grained adaptation. |
Opinions in Interactions : New Annotations of the SEMAINE Database (2022.lrec-1)
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| Challenge: | a new method for the detection of opinions in interactions is proposed . a dataset of dyadic interactions is annotated continuously in two affective dimensions related to the emotions . |
| Approach: | They propose to annotate opinions over a multimodal corpus of dyadic interactions . they use a d-acting algorithm to annnotate the opinions of a speaker . |
| Outcome: | The proposed method allows to obtain a precise annotation regarding the opinion of a speaker. |