mlsanityData to 14 Oct 2026

JPIS: A Joint Model for Profile-based Intent Detection and Slot Filling with Slot-to-Intent Attention

arXiv 2312.08737 ↗First posted 14 Dec 2023cs.CLcited by 2

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Abstract (arXiv)

Profile-based intent detection and slot filling are important tasks aimed at reducing the ambiguity in user utterances by leveraging user-specific supporting profile information. However, research in these two tasks has not been extensively explored. To fill this gap, we propose a joint model, namely JPIS, designed to enhance profile-based intent detection and slot filling. JPIS incorporates the supporting profile information into its encoder and introduces a slot-to-intent attention mechanism to transfer slot information representations to intent detection. Experimental results show that our JPIS substantially outperforms previous profile-based models, establishing a new state-of-the-art performance in overall accuracy on the Chinese benchmark dataset ProSLU.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 21 of its 28 references that are in the map. First posted on arXiv 14 Dec 2023.

Builds on

21 of 28 references.

References · 21

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  11. 2019A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Fillingcited by 85
  12. 2018Joint Slot Filling and Intent Detection via Capsule Neural Networkscited by 73
9 more
  1. 2018A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Fillingcited by 53
  2. 2020Inferring Degrees from Incomplete Networks and Nonlinear Dynamicscited by 33
  3. 2021GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Fillingcited by 33
  4. 2021Intent Detection and Slot Filling for Vietnamesecited by 19
  5. 2021Joint Multiple Intent Detection and Slot Filling via Self-distillationcited by 12
  6. 2022A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understandingcited by 9
  7. 2021Text is no more Enough! A Benchmark for Profile-based Spoken Language Understandingcited by 7
  8. 2023MISCA: A Joint Model for Multiple Intent Detection and Slot Filling with Intent-Slot Co-Attentioncited by 7
  9. 2021Joint Intent Detection And Slot Filling Based on Continual Learning Modelcited by 4

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Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025AFD-SLU: Adaptive Feature Distillation for Spoken Language Understandingcited by 1
  2. 2025Introducing Visual Scenes and Reasoning: A More Realistic Benchmark for Spoken Language Understandingcited by 1