Slot Filling On Mixsnips

Métriques

Micro F1

Résultats

Résultats de performance de divers modèles sur ce benchmark

		Paper Title
BiSLU	97.2	Joint Multiple Intent Detection and Slot Filling with Supervised Contrastive Learning and Self-Distillation
SLIM (PACL)	96.8	A Two-Stage Prediction-Aware Contrastive Learning Framework for Multi-Intent NLU
SLIM	96.5	SLIM: Explicit Slot-Intent Mapping with BERT for Joint Multi-Intent Detection and Slot Filling
Uni-MIS	96.4	Uni-MIS: United Multiple Intent Spoken Language Understanding via Multi-View Intent-Slot Interaction
TFMN	96.4	A Transformer-based Threshold-Free Framework for Multi-Intent NLU
TFMN (PACL)	96.3	A Two-Stage Prediction-Aware Contrastive Learning Framework for Multi-Intent NLU
RoBERTa (PACL)	96.2	A Two-Stage Prediction-Aware Contrastive Learning Framework for Multi-Intent NLU
DGIF	95.9	A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding
SSRAN	95.8	A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding
MISCA	95.2	MISCA: A Joint Model for Multiple Intent Detection and Slot Filling with Intent-Slot Co-Attention
Co-guiding Net	95.1	Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphs
UGEN	95.0	Incorporating Instructional Prompts into a Unified Generative Framework for Joint Multiple Intent Detection and Slot Filling
Global Intent-Slot Co-occurence	95.0	Enhancing Joint Multiple Intent Detection and Slot Filling with Global Intent-Slot Co-occurrence
GL-GIN	94.9	GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Filling
AGIF	94.5	AGIF: An Adaptive Graph-Interactive Framework for Joint Multiple Intent Detection and Slot Filling
Topic Information	94.4	Exploiting Topic Information for Joint Intent Detection and Slot Filling

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Slot Filling On Mixsnips | SOTA | HyperAI