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

arXiv: https://arxiv.org/abs/2106.01925 · HTML: https://mlsanity.com/paper/2106.01925/

## Key facts

- Cited by 33 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 41 references that are in the map.
- First posted on arXiv 3 Jun 2021.

## Builds on (most cited first, 25 of 25)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Graph Attention Networks](https://mlsanity.com/paper/1710.10903/) (2017)
- [Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces](https://mlsanity.com/paper/1805.10190/) (2018)
- [Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling](https://mlsanity.com/paper/1609.01454/) (2016)
- [Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey](https://mlsanity.com/paper/2105.04387/) (2021)
- [A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding](https://mlsanity.com/paper/1909.02188/) (2019)
- [A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling](https://mlsanity.com/paper/1907.00390/) (2019)
- [Joint Slot Filling and Intent Detection via Capsule Neural Networks](https://mlsanity.com/paper/1812.09471/) (2018)
- [A Co-Interactive Transformer for Joint Slot Filling and Intent Detection](https://mlsanity.com/paper/2010.03880/) (2020)
- [Graph-based Neural Multi-Document Summarization](https://mlsanity.com/paper/1706.06681/) (2017)
- [Zero-shot User Intent Detection via Capsule Neural Networks](https://mlsanity.com/paper/1809.00385/) (2018)
- [A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling](https://mlsanity.com/paper/1812.10235/) (2018)
- [A Survey on Spoken Language Understanding: Recent Advances and New Frontiers](https://mlsanity.com/paper/2103.03095/) (2021)
- [SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling](https://mlsanity.com/paper/2010.02693/) (2020)
- [Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks](https://mlsanity.com/paper/1909.02606/) (2019)
- [Empirical Analysis of Unlabeled Entity Problem in Named Entity Recognition](https://mlsanity.com/paper/2012.05426/) (2020)
- [CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding](https://mlsanity.com/paper/1909.06937/) (2019)
- [Co-GAT: A Co-Interactive Graph Attention Network for Joint Dialog Act Recognition and Sentiment Classification](https://mlsanity.com/paper/2012.13260/) (2020)
- [Incorporating Commonsense Knowledge into Abstractive Dialogue Summarization via Heterogeneous Graph Networks](https://mlsanity.com/paper/2010.10044/) (2020)
- [Contextualized Non-local Neural Networks for Sequence Learning](https://mlsanity.com/paper/1811.08600/) (2018)
- [Injecting Word Information with Multi-Level Word Adapter for Chinese Spoken Language Understanding](https://mlsanity.com/paper/2010.03903/) (2020)
- [Graph Convolutional Networks for Named Entity Recognition](https://mlsanity.com/paper/1709.10053/) (2017)
- [DRTS Parsing with Structure-Aware Encoding and Decoding](https://mlsanity.com/paper/2005.06901/) (2020)

## Built on by (most cited first, 30 of 33)

- [A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond](https://mlsanity.com/paper/2204.09269/) (2022)
- [A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods](https://mlsanity.com/paper/2204.03508/) (2022)
- [Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphs](https://mlsanity.com/paper/2210.10375/) (2022)
- [Group is better than individual: Exploiting Label Topologies and Label Relations for Joint Multiple Intent Detection and Slot Filling](https://mlsanity.com/paper/2210.10369/) (2022)
- [A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding](https://mlsanity.com/paper/2211.04023/) (2022)
- [Text is no more Enough! A Benchmark for Profile-based Spoken Language Understanding](https://mlsanity.com/paper/2112.11953/) (2021)
- [Towards a Progression-Aware Autonomous Dialogue Agent](https://mlsanity.com/paper/2205.03692/) (2022)
- [Relational Temporal Graph Reasoning for Dual-task Dialogue Language Understanding](https://mlsanity.com/paper/2306.09114/) (2023)
- [Joint Multiple Intent Detection and Slot Filling with Supervised Contrastive Learning and Self-Distillation](https://mlsanity.com/paper/2308.14654/) (2023)
- [MISCA: A Joint Model for Multiple Intent Detection and Slot Filling with Intent-Slot Co-Attention](https://mlsanity.com/paper/2312.05741/) (2023)
- [ECLM: Entity Level Language Model for Spoken Language Understanding with Chain of Intent](https://mlsanity.com/paper/2403.04481/) (2024)
- [BlendX: Complex Multi-Intent Detection with Blended Patterns](https://mlsanity.com/paper/2403.18277/) (2024)
- [Know Your Intent: An Autonomous Multi-Perspective LLM Agent Framework for DeFi User Transaction Intent Mining](https://mlsanity.com/paper/2511.15456/) (2025)
- [A Unified Framework for Multi-intent Spoken Language Understanding with prompting](https://mlsanity.com/paper/2210.03337/) (2022)
- [A Scope Sensitive and Result Attentive Model for Multi-Intent Spoken Language Understanding](https://mlsanity.com/paper/2211.12220/) (2022)
- [A Pointer Network-based Approach for Joint Extraction and Detection of Multi-Label Multi-Class Intents](https://mlsanity.com/paper/2410.22476/) (2024)
- [Capture Salient Historical Information: A Fast and Accurate Non-Autoregressive Model for Multi-turn Spoken Language Understanding](https://mlsanity.com/paper/2206.12209/) (2022)
- [OpenSLU: A Unified, Modularized, and Extensible Toolkit for Spoken Language Understanding](https://mlsanity.com/paper/2305.10231/) (2023)
- [Adaptive End-to-End Metric Learning for Zero-Shot Cross-Domain Slot Filling](https://mlsanity.com/paper/2310.15294/) (2023)
- [Co-guiding for Multi-intent Spoken Language Understanding](https://mlsanity.com/paper/2312.03716/) (2023)
- [JPIS: A Joint Model for Profile-based Intent Detection and Slot Filling with Slot-to-Intent Attention](https://mlsanity.com/paper/2312.08737/) (2023)
- [A Two-Stage Prediction-Aware Contrastive Learning Framework for Multi-Intent NLU](https://mlsanity.com/paper/2405.02925/) (2024)
- [MIDAS: Multi-level Intent, Domain, And Slot Knowledge Distillation for Multi-turn NLU](https://mlsanity.com/paper/2408.08144/) (2024)
- [A Chit-Chats Enhanced Task-Oriented Dialogue Corpora for Fuse-Motive Conversation Systems](https://mlsanity.com/paper/2205.05886/) (2022)
- [ESIE-BERT: Enriching Sub-words Information Explicitly with BERT for Joint Intent Classification and SlotFilling](https://mlsanity.com/paper/2211.14829/) (2022)
- [AFD-SLU: Adaptive Feature Distillation for Spoken Language Understanding](https://mlsanity.com/paper/2509.04821/) (2025)
- [Generalized Multiple Intent Conditioned Slot Filling](https://mlsanity.com/paper/2305.11023/) (2023)
- [I2KD-SLU: An Intra-Inter Knowledge Distillation Framework for Zero-Shot Cross-Lingual Spoken Language Understanding](https://mlsanity.com/paper/2310.02594/) (2023)
- [HC2L: Hybrid and Cooperative Contrastive Learning for Cross-lingual Spoken Language Understanding](https://mlsanity.com/paper/2405.06204/) (2024)
- [Towards Spoken Language Understanding via Multi-level Multi-grained Contrastive Learning](https://mlsanity.com/paper/2405.20852/) (2024)

## 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.