DecoStrat: Leveraging the Capabilities of Language Models in D2T Generation via Decoding Framework Article Swipe
Elias Lemuye Jimale
,
Wenyu Chen
,
Mugahed A. Al–antari
,
Yeong Hyeon Gu
,
Victor Kwaku Agbesi
,
Wasif Feroze
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/math12223596
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/math12223596
Current language models have achieved remarkable success in NLP tasks. Nonetheless, individual decoding methods face difficulties in realizing the immense potential of these models. The challenge is primarily due to the lack of a decoding framework that can integrate language models and decoding methods. We introduce DecoStrat, which bridges the gap between language modeling and the decoding process in D2T generation. By leveraging language models, DecoStrat facilitates the exploration of alternative decoding methods tailored to specific tasks. We fine-tuned the model on the MultiWOZ dataset to meet task-specific requirements and employed it to generate output(s) through multiple interactive modules of the framework. The Director module orchestrates the decoding processes, engaging the Generator to produce output(s) text based on the selected decoding method and input data. The Manager module enforces a selection strategy, integrating Ranker and Selector to identify the optimal result. Evaluations on the stated dataset show that DecoStrat effectively produces a diverse and accurate output, with MBR variants consistently outperforming other methods. DecoStrat with the T5-small model surpasses some baseline frameworks. Generally, the findings highlight DecoStrat’s potential for optimizing decoding methods in diverse real-world applications.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/math12223596
- https://www.mdpi.com/2227-7390/12/22/3596/pdf?version=1731838453
- OA Status
- gold
- Cited By
- 1
- References
- 48
- Related Works
- 10
- OpenAlex ID
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DecoStrat: Leveraging the Capabilities of Language Models in D2T Generation via Decoding FrameworkWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
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2024Year of publication
- Publication date
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2024-11-17Full publication date if available
- Authors
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Elias Lemuye Jimale, Wenyu Chen, Mugahed A. Al–antari, Yeong Hyeon Gu, Victor Kwaku Agbesi, Wasif FerozeList of authors in order
- Landing page
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https://doi.org/10.3390/math12223596Publisher landing page
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https://www.mdpi.com/2227-7390/12/22/3596/pdf?version=1731838453Direct link to full text PDF
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2227-7390/12/22/3596/pdf?version=1731838453Direct OA link when available
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Decoding methods, Computer science, Computer architecture, Programming language, TelecommunicationsTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2112824353, https://openalex.org/W4231288952, https://openalex.org/W2135363470, https://openalex.org/W2003170434, https://openalex.org/W2981780252, https://openalex.org/W2739874095, https://openalex.org/W3022814719, https://openalex.org/W6769627184, https://openalex.org/W2982399380, https://openalex.org/W4303856695, https://openalex.org/W4378377586, https://openalex.org/W6761551260, https://openalex.org/W4296713955, https://openalex.org/W3196347491, https://openalex.org/W3005440057, https://openalex.org/W3016531961, https://openalex.org/W6754937296, https://openalex.org/W2948665450, https://openalex.org/W4389009377, https://openalex.org/W3027871355, https://openalex.org/W2798664956, https://openalex.org/W2100238596, https://openalex.org/W3160224178, https://openalex.org/W4328099923, https://openalex.org/W2951038425, https://openalex.org/W3026997957, https://openalex.org/W3200663532, https://openalex.org/W2798493043, https://openalex.org/W2136657878, https://openalex.org/W4309137656, https://openalex.org/W2566623769, https://openalex.org/W3119783931, https://openalex.org/W4253090545, https://openalex.org/W2160233880, https://openalex.org/W2954460650, https://openalex.org/W2889263348, https://openalex.org/W3115021520, https://openalex.org/W6682631176, https://openalex.org/W2123301721, https://openalex.org/W1956340063, https://openalex.org/W3034557228, https://openalex.org/W3107855336, https://openalex.org/W2992347006, https://openalex.org/W2979826702, https://openalex.org/W3197574297, https://openalex.org/W3007894275, https://openalex.org/W1522301498, https://openalex.org/W2157331557 |
| referenced_works_count | 48 |
| abstract_inverted_index.a | 33, 129, 151 |
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| abstract_inverted_index.MBR | 157 |
| abstract_inverted_index.NLP | 8 |
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| abstract_inverted_index.method | 121 |
| abstract_inverted_index.models | 2, 40 |
| abstract_inverted_index.module | 104, 127 |
| abstract_inverted_index.stated | 144 |
| abstract_inverted_index.tasks. | 9, 76 |
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| abstract_inverted_index.Manager | 126 |
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| abstract_inverted_index.methods | 13, 72, 181 |
| abstract_inverted_index.models, | 64 |
| abstract_inverted_index.models. | 23 |
| abstract_inverted_index.modules | 98 |
| abstract_inverted_index.optimal | 139 |
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| abstract_inverted_index.produce | 113 |
| abstract_inverted_index.result. | 140 |
| abstract_inverted_index.success | 6 |
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| abstract_inverted_index.MultiWOZ | 83 |
| abstract_inverted_index.Selector | 135 |
| abstract_inverted_index.T5-small | 166 |
| abstract_inverted_index.accurate | 154 |
| abstract_inverted_index.achieved | 4 |
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| abstract_inverted_index.decoding | 12, 34, 42, 56, 71, 107, 120, 180 |
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| abstract_inverted_index.language | 1, 39, 52, 63 |
| abstract_inverted_index.methods. | 43, 162 |
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| abstract_inverted_index.DecoStrat | 65, 148, 163 |
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| corresponding_author_ids | https://openalex.org/A5022092645, https://openalex.org/A5022731366, https://openalex.org/A5100687323 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I150229711, https://openalex.org/I28777354 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.49000000953674316 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.73048516 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |