Papers with token-by-token
Attending to Future Tokens for Bidirectional Sequence Generation (D19-1)
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| Challenge: | Neural sequence generation is typically performed token-by-token and left-to-right. |
| Approach: | They propose to use placeholder tokens to make the sequence generation process bidirectional by taking past and future tokens into consideration when generating the actual output token. |
| Outcome: | The proposed approach outperforms baselines on two conversational tasks by a large margin. |
Multilingual Autoregressive Entity Linking (2022.tacl-1)
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Nicola De Cao, Ledell Wu, Kashyap Popat, Mikel Artetxe, Naman Goyal, Mikhail Plekhanov, Luke Zettlemoyer, Nicola Cancedda, Sebastian Riedel, Fabio Petroni
| Challenge: | mGENRE is a sequence-to-sequence system for multilingual entity linking . mGenRE is used to solve language-specific mentions to a multilingual Knowledge Base . |
| Approach: | They propose a sequence-to-sequence system for multilingual entity linking . they match language-specific mentions against a multilingual Knowledge Base (KB) mGENRE is a sequential system that predicts the name of the target entity token-by-token . |
| Outcome: | The proposed system improves on three popular MEL benchmarks and shows improvements in accuracy. |
CopyNE: Better Contextual ASR by Copying Named Entities (2024.acl-long)
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| Challenge: | Existing approaches to transcribe contextual named entities (NEs) treat entities as tokens and generate them token-by-token, which may result in incomplete transcriptions of entities. |
| Approach: | They propose a mechanism that can copy entities from the NE dictionary and reduce errors during entity transcription. |
| Outcome: | The proposed mechanism can copy entities from the NE dictionary, reducing errors during entity transcription, ensuring the completeness of the entity. |
Interpretable Math Word Problem Solution Generation via Step-by-step Planning (2023.acl-long)
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| Challenge: | Existing approaches to solving math word problems focus on obtaining the correct answer. |
| Approach: | They propose a step-by-step planning approach for intermediate solution generation that strategically plans the generation of the next solution step based on the MWP and the previous solution steps. |
| Outcome: | The proposed approach improves the accuracy and interpretability of the solution on automatic metrics and human evaluation. |