Papers with hierarchical encoding
Improvement in Sign Language Translation Using Text CTC Alignment (2025.coling-main)
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| Challenge: | Current sign language translation (SLT) approaches rely on gloss-based supervision with Connectionist Temporal Classification (CTC) limiting their ability to handle non-monotonic alignments between sign language video and spoken text. |
| Approach: | They propose a method that integrates CTC/Attention with the attention mechanism during decoding and integrates it with the sign language video and spoken text. |
| Outcome: | The proposed method outperforms the pure-attention baseline and achieves comparable results to state-of-the-art methods. |
Pretrained Language Models for Sequential Sentence Classification (D19-1)
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| Challenge: | Recent successful models for document-level understanding have used hierarchical encoding and CRFs to capture dependencies between subsequent labels. |
| Approach: | They propose a pretrained language model that captures contextual dependencies without hierarchical encoding nor a CRF. |
| Outcome: | The proposed model captures contextual dependencies without hierarchical encoding nor a CRF on four datasets, including a new dataset of structured scientific abstracts. |
Semi-Structured Object Sequence Encoders (2023.findings-emnlp)
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Rudra Murthy, Riyaz Bhat, Chulaka Gunasekara, Siva Patel, Hui Wan, Tejas Dhamecha, Danish Contractor, Marina Danilevsky
| Challenge: | Semi-structured object sequences are often represented as a sequence of key-value pairs over time . authors propose a two-part approach that takes each key independently and encodes a representation of its values over time. |
| Approach: | They propose a two-part approach that first considers each key independently and encodes a representation of its values over time. |
| Outcome: | The proposed approach outperforms existing methods on multiple prediction tasks using real-world data. |