mlsanityData to 7 Oct 2026

GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Filling

arXiv 2106.01925 ↗First posted 3 Jun 2021cs.CLcited by 33

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Abstract (arXiv)

Multi-intent SLU can handle multiple intents in an utterance, which has attracted increasing attention. However, the state-of-the-art joint models heavily rely on autoregressive approaches, resulting in two issues: slow inference speed and information leakage. In this paper, we explore a non-autoregressive model for joint multiple intent detection and slot filling, achieving more fast and accurate. Specifically, we propose a Global-Locally Graph Interaction Network (GL-GIN) where a local slot-aware graph interaction layer is proposed to model slot dependency for alleviating uncoordinated slots problem while a global intent-slot graph interaction layer is introduced to model the interaction between multiple intents and all slots in the utterance. Experimental results on two public datasets show that our framework achieves state-of-the-art performance while being 11.5 times faster.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). Builds on 25 of its 41 references that are in the map. First posted on arXiv 3 Jun 2021.

Builds on

25 of 41 references.

References · 25

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  4. 2017Graph Attention Networkscited by 8,854
  5. 2018Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfacescited by 376
  6. 2016Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Fillingcited by 137
  7. 2021Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Surveycited by 130
  8. 2019A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understandingcited by 106
  9. 2019A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Fillingcited by 85
  10. 2018Joint Slot Filling and Intent Detection via Capsule Neural Networkscited by 73
  11. 2020A Co-Interactive Transformer for Joint Slot Filling and Intent Detectioncited by 61
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13 more
  1. 2018Zero-shot User Intent Detection via Capsule Neural Networkscited by 54
  2. 2018A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Fillingcited by 53
  3. 2021A Survey on Spoken Language Understanding: Recent Advances and New Frontierscited by 53
  4. 2020SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Fillingcited by 42
  5. 2019Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networkscited by 39
  6. 2019CM-Net: A Novel Collaborative Memory Network for Spoken Language Understandingcited by 34
  7. 2020Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognitioncited by 34
  8. 2020Co-GAT: A Co-Interactive Graph Attention Network for Joint Dialog Act Recognition and Sentiment Classificationcited by 29
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 11; 2023: 9; 2024: 7; 2025: 3; 2026: 2.

33 papers.

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  1. 2022A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyondcited by 64
  2. 2022A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methodscited by 42
  3. 2022Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphscited by 14
  4. 2022Group is better than individual: Exploiting Label Topologies and Label Relations for Joint Multiple Intent Detection and Slot Fillingcited by 10
  5. 2022A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understandingcited by 9
  6. 2021Text is no more Enough! A Benchmark for Profile-based Spoken Language Understandingcited by 7
  7. 2022Towards a Progression-Aware Autonomous Dialogue Agentcited by 7
  8. 2023Relational Temporal Graph Reasoning for Dual-task Dialogue Language Understandingcited by 7
  9. 2023Joint Multiple Intent Detection and Slot Filling with Supervised Contrastive Learning and Self-Distillationcited by 7
  10. 2023MISCA: A Joint Model for Multiple Intent Detection and Slot Filling with Intent-Slot Co-Attentioncited by 7
  11. 2024ECLM: Entity Level Language Model for Spoken Language Understanding with Chain of Intentcited by 7
  12. 2024BlendX: Complex Multi-Intent Detection with Blended Patternscited by 4
21 more
  1. 2025Know Your Intent: An Autonomous Multi-Perspective LLM Agent Framework for DeFi User Transaction Intent Miningcited by 4
  2. 2022A Unified Framework for Multi-intent Spoken Language Understanding with promptingcited by 3
  3. 2022A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understandingcited by 3
  4. 2024A Pointer Network-based Approach for Joint Extraction and Detection of Multi-Label Multi-Class Intentscited by 3
  5. 2022Capture Salient Historical Information: A Fast and Accurate Non-Autoregressive Model for Multi-turn Spoken Language Understandingcited by 2
  6. 2023OpenSLU: A Unified, Modularized, and Extensible Toolkit for Spoken Language Understandingcited by 2
  7. 2023Adaptive End-to-End Metric Learning for Zero-Shot Cross-Domain Slot Fillingcited by 2
  8. 2023Co-guiding for Multi-intent Spoken Language Understandingcited by 2
  9. 2023JPIS: A Joint Model for Profile-based Intent Detection and Slot Filling with Slot-to-Intent Attentioncited by 2
  10. 2024A Two-Stage Prediction-Aware Contrastive Learning Framework for Multi-Intent NLUcited by 2
  11. 2024MIDAS: Multi-level Intent, Domain, And Slot Knowledge Distillation for Multi-turn NLUcited by 2
  12. 2022A Chit-Chats Enhanced Task-Oriented Dialogue Corpora for Fuse-Motive Conversation Systemscited by 1
  13. 2022ESIE-BERT: Enriching Sub-words Information Explicitly with BERT for Joint Intent Classification and SlotFillingcited by 1
  14. 2025AFD-SLU: Adaptive Feature Distillation for Spoken Language Understandingcited by 1
  15. 2023Generalized Multiple Intent Conditioned Slot Fillingcited by 0
  16. 2023I2KD-SLU: An Intra-Inter Knowledge Distillation Framework for Zero-Shot Cross-Lingual Spoken Language Understandingcited by 0
  17. 2024HC2L: Hybrid and Cooperative Contrastive Learning for Cross-lingual Spoken Language Understandingcited by 0
  18. 2024Towards Spoken Language Understanding via Multi-level Multi-grained Contrastive Learningcited by 0
  19. 2025Multi-Intent Spoken Language Understanding: Methods, Trends, and Challengescited by 0
  20. 2026A Generative Model for Joint Multiple Intent Detection and Slot Fillingcited by 0
  21. 2026Known Intents, New Combinations: Clause-Factorized Decoding for Compositional Multi-Intent Detectioncited by 0