Outputs for Fine-Tuning with Divergent Chains of Thought Boosts Reasoning Through Self-Correction in Language Models
| dc.contributor.author | Puerto, Haritz | |
| dc.contributor.author | Chubakov, Tilek | |
| dc.contributor.author | Zhu, Xiaodan | |
| dc.contributor.author | Tayyar Madabushi, Harish | |
| dc.contributor.author | Gurevych, Iryna | |
| dc.date.accessioned | 2024-06-21T19:50:53Z | |
| dc.date.available | 2024-06-21T19:50:53Z | |
| dc.date.issued | 2024-06 | |
| dc.identifier.uri | https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4266 | |
| dc.description | Raw responses from the models, clean answers, post-processed predictions and evaluation results for each model and dataset using in the publication Fine-Tuning with Divergent Chains of Thought Boosts Reasoning Through Self-Correction in Language Models | de_DE |
| dc.language.iso | en | de_DE |
| dc.rights | CC BY-SA 3.0 | |
| dc.rights.uri | https://creativecommons.org/licenses/by-sa/3.0/deed.en | |
| dc.subject | chain of thought | de_DE |
| dc.subject | cot | de_DE |
| dc.subject | large language model | de_DE |
| dc.subject | llm | de_DE |
| dc.subject | NLP | de_DE |
| dc.subject.classification | 4.43-04 Künstliche Intelligenz und Maschinelle Lernverfahren | de_DE |
| dc.subject.classification | 4.43-05 Bild- und Sprachverarbeitung, Computergraphik und Visualisierung, Human Computer Interaction, Ubiquitous und Wearable Computing | |
| dc.subject.ddc | 004 | |
| dc.title | Outputs for Fine-Tuning with Divergent Chains of Thought Boosts Reasoning Through Self-Correction in Language Models | de_DE |
| dc.type | Dataset | de_DE |
| dc.description.version | 1.0 | de_DE |
| tud.unit | TUDa | |
| tud.history.classification | Version=2016-2020;409-05 Interaktive und intelligente Systeme, Bild- und Sprachverarbeitung, Computergraphik und Visualisierung |
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