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Aspect-Based Sentiment Analysis (ABSA) 벤치마크

Aspect-Based Sentiment Analysis (ABSA) on ASQP

24개 결과 · ⬇ CSV · JSON

F1 (R15)

22.87 30.21 37.54 44.88 52.21 2021-08 2026-09 GAS — 45.98 (2021-08-01) GAS — 45.98 (2021-08-01) Paraphrase — 46.93 (2021-10-02) TAS-BRET — 34.78 (2021-10-02) Paraphrase — 46.93 (2021-10-02) TAS-BRET — 34.78 (2021-10-02) DLO — 48.18 (2022-10-19) DLO — 48.18 (2022-10-19) MvP (multi-task) — 52.21 (2023-05-22) MvP — 51.04 (2023-05-22) ChatGPT (gpt-3.5-turbo, few-shot) — 34.27 (2023-05-22) ChatGPT (gpt-3.5-turbo, zero-shot) — 22.87 (2023-05-22) MvP (multi-task) — 52.21 (2023-05-22) MvP — 51.04 (2023-05-22) ChatGPT (gpt-3.5-turbo, few-shot) — 34.27 (2023-05-22) ChatGPT (gpt-3.5-turbo, zero-shot) — 22.87 (2023-05-22) AugABSA — 50.01 (2023-07-01) AugABSA — 50.01 (2023-07-01) Gemma-3-27B (50-shot, self-consistency learning) — 41.74 (2025-02-18) Gemma-3-27B (10-shot, self-consistency learning) — 39.95 (2025-02-18) Gemma-3-27B (50-shot, self-consistency learning) — 41.74 (2025-02-18) Gemma-3-27B (10-shot, self-consistency learning) — 39.95 (2025-02-18) GAS — 45.98 (2021-08-01) Paraphrase — 46.93 (2021-10-02) DLO — 48.18 (2022-10-19) MvP (multi-task) — 52.21 (2023-05-22)
RankModel F1 (R15)F1 (R16) PaperCodeYear
21 Gemma-3-27B (10-shot, self-consistency learning) 39.9546.23 Do we still need Human Annotators? Prompting Large Language Models for Aspect Sentiment Quad Prediction NilsHellwig/llm-prompting-asqp 2025
22 TAS-BRET 34.7843.71 Aspect Sentiment Quad Prediction as Paraphrase Generation isakzhang/absa-quad 2021
23 ChatGPT (gpt-3.5-turbo, few-shot) 34.27 MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction ZubinGou/multi-view-prompting 2023
24 ChatGPT (gpt-3.5-turbo, zero-shot) 22.87 MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction ZubinGou/multi-view-prompting 2023
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