# Joint Slot Filling and Intent Detection via Capsule Neural Networks

arXiv: https://arxiv.org/abs/1812.09471 · HTML: https://mlsanity.com/paper/1812.09471/

## Key facts

- Cited by 73 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Dec 2018.

## Built on by (most cited first, 30 of 73)

- [A Survey on Spoken Language Understanding: Recent Advances and New Frontiers](https://mlsanity.com/paper/2103.03095/) (2021)
- [Visual Goal-Step Inference using wikiHow](https://mlsanity.com/paper/2104.05845/) (2021)
- [A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods](https://mlsanity.com/paper/2204.03508/) (2022)
- [MIntRec: A New Dataset for Multimodal Intent Recognition](https://mlsanity.com/paper/2209.04355/) (2022)
- [GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Filling](https://mlsanity.com/paper/2106.01925/) (2021)
- [MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations](https://mlsanity.com/paper/2403.10943/) (2024)
- [Generalized Zero-shot Intent Detection via Commonsense Knowledge](https://mlsanity.com/paper/2102.02925/) (2021)
- [Intent Detection and Slot Filling for Vietnamese](https://mlsanity.com/paper/2104.02021/) (2021)
- [CoF-CoT: Enhancing Large Language Models with Coarse-to-Fine Chain-of-Thought Prompting for Multi-domain NLU Tasks](https://mlsanity.com/paper/2310.14623/) (2023)
- [Non-Autoregressive Semantic Parsing for Compositional Task-Oriented Dialog](https://mlsanity.com/paper/2104.04923/) (2021)
- [Learning Discriminative Representations and Decision Boundaries for Open Intent Detection](https://mlsanity.com/paper/2203.05823/) (2022)
- [CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detection](https://mlsanity.com/paper/2106.06213/) (2021)
- [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)
- [Linguistically-Enriched and Context-Aware Zero-shot Slot Filling](https://mlsanity.com/paper/2101.06514/) (2021)
- [Lifelong Intent Detection via Multi-Strategy Rebalancing](https://mlsanity.com/paper/2108.04445/) (2021)
- [Workflow Discovery from Dialogues in the Low Data Regime](https://mlsanity.com/paper/2205.11690/) (2022)
- [Towards Joint Intent Detection and Slot Filling via Higher-order Attention](https://mlsanity.com/paper/2109.08890/) (2021)
- [SLIM: Explicit Slot-Intent Mapping with BERT for Joint Multi-Intent Detection and Slot Filling](https://mlsanity.com/paper/2108.11711/) (2021)
- [Learning with Capsules: A Survey](https://mlsanity.com/paper/2206.02664/) (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)
- [Distilling EEG Representations via Capsules for Affective Computing](https://mlsanity.com/paper/2105.00104/) (2021)
- [Bi-directional Joint Neural Networks for Intent Classification and Slot Filling](https://mlsanity.com/paper/2202.13079/) (2022)
- [Relational Temporal Graph Reasoning for Dual-task Dialogue Language Understanding](https://mlsanity.com/paper/2306.09114/) (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)
- [Masked Conditional Random Fields for Sequence Labeling](https://mlsanity.com/paper/2103.10682/) (2021)
- [Learning to Bridge Metric Spaces: Few-shot Joint Learning of Intent Detection and Slot Filling](https://mlsanity.com/paper/2106.07343/) (2021)
- [A Question-answering Based Framework for Relation Extraction Validation](https://mlsanity.com/paper/2104.02934/) (2021)
- [An Effective Non-Autoregressive Model for Spoken Language Understanding](https://mlsanity.com/paper/2108.07005/) (2021)
- [Learning to Classify Open Intent via Soft Labeling and Manifold Mixup](https://mlsanity.com/paper/2204.07804/) (2022)

## Abstract (arXiv)

Being able to recognize words as slots and detect the intent of an utterance has been a keen issue in natural language understanding. The existing works either treat slot filling and intent detection separately in a pipeline manner, or adopt joint models which sequentially label slots while summarizing the utterance-level intent without explicitly preserving the hierarchical relationship among words, slots, and intents. To exploit the semantic hierarchy for effective modeling, we propose a capsule-based neural network model which accomplishes slot filling and intent detection via a dynamic routing-by-agreement schema. A re-routing schema is proposed to further synergize the slot filling performance using the inferred intent representation. Experiments on two real-world datasets show the effectiveness of our model when compared with other alternative model architectures, as well as existing natural language understanding services.