Assessing Open-Source Large Language Models on Argumentation Mining Subtasks
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866915009981841408 |
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| author | Abkenar, Mohammad Yeghaneh Wang, Weixing Graupner, Hendrik Stede, Manfred |
| author_facet | Abkenar, Mohammad Yeghaneh Wang, Weixing Graupner, Hendrik Stede, Manfred |
| contents | We explore the capability of four open-sourcelarge language models (LLMs) in argumentation mining (AM). We conduct experiments on three different corpora; persuasive essays(PE), argumentative microtexts (AMT) Part 1 and Part 2, based on two argumentation mining sub-tasks: (i) argumentative discourse units classifications (ADUC), and (ii) argumentative relation classification (ARC). This work aims to assess the argumentation capability of open-source LLMs, including Mistral 7B, Mixtral8x7B, LlamA2 7B and LlamA3 8B in both, zero-shot and few-shot scenarios. Our analysis contributes to further assessing computational argumentation with open-source LLMs in future research efforts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_05639 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Assessing Open-Source Large Language Models on Argumentation Mining Subtasks Abkenar, Mohammad Yeghaneh Wang, Weixing Graupner, Hendrik Stede, Manfred Computation and Language We explore the capability of four open-sourcelarge language models (LLMs) in argumentation mining (AM). We conduct experiments on three different corpora; persuasive essays(PE), argumentative microtexts (AMT) Part 1 and Part 2, based on two argumentation mining sub-tasks: (i) argumentative discourse units classifications (ADUC), and (ii) argumentative relation classification (ARC). This work aims to assess the argumentation capability of open-source LLMs, including Mistral 7B, Mixtral8x7B, LlamA2 7B and LlamA3 8B in both, zero-shot and few-shot scenarios. Our analysis contributes to further assessing computational argumentation with open-source LLMs in future research efforts. |
| title | Assessing Open-Source Large Language Models on Argumentation Mining Subtasks |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2411.05639 |