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SotA/Natural Language Processing/Intent Detection/MixSNIPS

Intent Detection on MixSNIPS

Metric: Accuracy (higher is better)

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#Model↕Accuracy▼Extra DataPaperDate↕Code
1SSRAN98.4NoA Scope Sensitive and Result Attentive Model for...2022-11-22-
2BiSLU97.8NoJoint Multiple Intent Detection and Slot Filling...2023-08-28Code
3DGIF97.8NoA Dynamic Graph Interactive Framework with Label...2022-11-08-
4TFMN97.7No---
5Co-guiding Net97.7NoCo-guiding Net: Achieving Mutual Guidances betwe...2022-10-19Code
6TFMN (PACL)97.4NoA Two-Stage Prediction-Aware Contrastive Learnin...2024-05-05-
7MISCA97.3NoMISCA: A Joint Model for Multiple Intent Detecti...2023-12-10Code
8Uni-MIS97.2No--Code
9SLIM97.2NoSLIM: Explicit Slot-Intent Mapping with BERT for...2021-08-26Code
10SLIM (PACL)96.9NoA Two-Stage Prediction-Aware Contrastive Learnin...2024-05-05-
11UGEN96.9No--Code
12AGIF96.5NoAGIF: An Adaptive Graph-Interactive Framework fo...2020-04-21Code
13RoBERTa (PACL)96.5NoA Two-Stage Prediction-Aware Contrastive Learnin...2024-05-05-
14Topic Information96.3No---
15GL-GIN95.6NoGL-GIN: Fast and Accurate Non-Autoregressive Mod...2021-06-03Code
16Global Intent-Slot Co-occurence95.5No--Code