Intent Detection

Intent Detection is a task of determining the underlying purpose or goal behind a user's search query given a context. The task plays a significant role in search and recommendations. A traditional approach for intent detection implies using an intent detector model to classify user search query into predefined intent categories, given a context. One of the key challenges of the task implies identifying user intents for cold-start sessions, i.e., search sessions initiated by a non-logged-in or unrecognized user.

Source: Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 101–125 of 330 papers

Title	Date	Tasks	Status	Score
Churn Intent Detection in Multilingual Chatbot Conversations and Social Media	Aug 25, 2018	ChatbotIntent Detection	CodeCode Available	5
Privacy Guarantees for De-identifying Text Transformations	Aug 7, 2020	BIG-bench Machine LearningDe-identification	CodeCode Available	5
HPERL: 3D Human Pose Estimation from RGB and LiDAR	Oct 16, 2020	3D Human Pose EstimationAction Recognition	CodeCode Available	5
Integrating Text and Image: Determining Multimodal Document Intent in Instagram Posts	Apr 19, 2019	Intent Detection	CodeCode Available	5
Question Embeddings Based on Shannon Entropy: Solving intent classification task in goal-oriented dialogue system	Mar 25, 2019	General Classificationintent-classification	CodeCode Available	5
ReCoMIF: Reading comprehension based multi-source information fusion network for Chinese spoken language understanding	Aug 1, 2023	Intent DetectionMultiple-choice	CodeCode Available	5
ChEDDAR: Student-ChatGPT Dialogue in EFL Writing Education	Sep 23, 2023	Intent DetectionTask-Oriented Dialogue Systems	CodeCode Available	5
A Weight-aware-based Multi-source Unsupervised Domain Adaptation Method for Human Motion Intention Recognition	Apr 19, 2024	Domain AdaptationIntent Detection	CodeCode Available	5
ed-cec: improving rare word recognition using asr postprocessing based on error detection and context-aware error correction	Oct 8, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	5
Effectiveness of Pre-training for Few-shot Intent Classification	Sep 13, 2021	Classificationintent-classification	CodeCode Available	5
ChatGPT as Data Augmentation for Compositional Generalization: A Case Study in Open Intent Detection	Aug 25, 2023	Data AugmentationIntent Detection	CodeCode Available	5
From Disfluency Detection to Intent Detection and Slot Filling	Sep 17, 2022	Intent DetectionLanguage Modeling	CodeCode Available	5
A Framework to Generate High-Quality Datapoints for Multiple Novel Intent Detection	May 4, 2022	Intent Detection	CodeCode Available	5
Sequence Labeling Approach to the Task of Sentence Boundary Detection	Jan 20, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	5
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding	May 15, 2021	intent-classificationIntent Classification	CodeCode Available	5
FuSSI-Net: Fusion of Spatio-temporal Skeletons for Intention Prediction Network	May 15, 2020	Autonomous DrivingIntent Detection	CodeCode Available	5
CAE: Mechanism to Diminish the Class Imbalanced in SLU Slot Filling Task	Sep 21, 2022	intent-classificationIntent Classification	CodeCode Available	5
Enhancing Joint Multiple Intent Detection and Slot Filling with Global Intent-Slot Co-occurrence	Dec 1, 2022	Graph Neural NetworkIntent Detection	CodeCode Available	5
Few-shot Pseudo-Labeling for Intent Detection	Dec 8, 2020	ClusteringIntent Detection	CodeCode Available	5
Deep Unknown Intent Detection with Margin Loss	Jun 2, 2019	Intent DetectionNovelty Detection	CodeCode Available	5
Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent Detection	Dec 14, 2021	Few-Shot LearningGeneralized Few-Shot Learning	CodeCode Available	5
Generate then Refine: Data Augmentation for Zero-shot Intent Detection	Oct 2, 2024	Data AugmentationDiversity	CodeCode Available	5
A Post-processing Method for Detecting Unknown Intent of Dialogue System via Pre-trained Deep Neural Network Classifier	Mar 7, 2020	Intent DetectionNovelty Detection	CodeCode Available	5
Towards Multi-label Unknown Intent Detection	Oct 1, 2022	Intent Detection	CodeCode Available	5
Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting Framework	Jun 10, 2025	Domain AdaptationIntent Detection	CodeCode Available	5

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All datasets ATIS MixSNIPS MixATIS SNIPS ASOS.com user intent BANKING77 ATIS (vi)BANKING77 10-shot BANKING77 5-shot CAIS CLINC150 CLINC150 10-shot

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Bi-model with decoder	Accuracy	98.99	—	Unverified
2	Transformer-Capsule	Accuracy	98.89	—	Unverified
3	Attention Encoder-Decoder NN	Accuracy	98.43	—	Unverified
4	Joint model with recurrent slot label context	Accuracy	98.4	—	Unverified
5	CTRAN	Accuracy	98.07	—	Unverified
6	Joint BERT + CRF	Accuracy	97.9	—	Unverified
7	SF-ID (BLSTM) network	Accuracy	97.76	—	Unverified
8	SF-ID	Accuracy	97.76	—	Unverified
9	JointBERT-CAE	Accuracy	97.5	—	Unverified
10	Stack-Propagation (+BERT)	Accuracy	97.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SSRAN	Accuracy	98.4	—	Unverified
2	BiSLU	Accuracy	97.8	—	Unverified
3	DGIF	Accuracy	97.8	—	Unverified
4	TFMN	Accuracy	97.7	—	Unverified
5	Co-guiding Net	Accuracy	97.7	—	Unverified
6	TFMN (PACL)	Accuracy	97.4	—	Unverified
7	MISCA	Accuracy	97.3	—	Unverified
8	Uni-MIS	Accuracy	97.2	—	Unverified
9	SLIM	Accuracy	97.2	—	Unverified
10	SLIM (PACL)	Accuracy	96.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DGIF	Accuracy	83.3	—	Unverified
2	UGEN	Accuracy	83	—	Unverified
3	TFMN (PACL)	Accuracy	82.9	—	Unverified
4	SLIM (PACL)	Accuracy	81.9	—	Unverified
5	BiSLU	Accuracy	81.5	—	Unverified
6	TFMN	Accuracy	79.8	—	Unverified
7	Co-guiding Net	Accuracy	79.1	—	Unverified
8	RoBERTa (PACL)	Accuracy	79.1	—	Unverified
9	Uni-MIS	Accuracy	78.5	—	Unverified
10	SLIM	Accuracy	78.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CTRAN	Accuracy	99.42	—	Unverified
2	Stack-Propagation (+BERT)	Accuracy	99	—	Unverified
3	JointBERT-CAE	Accuracy	98.3	—	Unverified
4	AGIF	Accuracy	98.1	—	Unverified
5	LIDSNet	Accuracy	98	—	Unverified
6	Stack-Propagation	Accuracy	98	—	Unverified
7	SF-ID	Accuracy	97.43	—	Unverified
8	SF-ID (BLSTM) network	Accuracy	97.43	—	Unverified
9	Capsule-NLU	Accuracy	97.3	—	Unverified
10	Slot-Gated BLSTM with Attension	Accuracy	97	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	plain-LSTM	F1	0.89	—	Unverified
2	linear-Ngrams	F1	0.87	—	Unverified
3	glove-LSTM	F1	0.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-Large + ICDA	Accuracy (%)	94.42	—	Unverified
2	OCaTS (kNN-GPT-4)	Accuracy (%)	82.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	JointBERT-CAE	Intent Accuracy	97.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-Large + ICDA	Accuracy (%)	89.79	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-Large + ICDA	Accuracy (%)	84.01	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CM-Net	Acc	94.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-Large + ICDA	Accuracy (%)	97.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-Large + ICDA	Accuracy (%)	94.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-Large + ICDA	Accuracy (%)	92.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIDAS	Accuracy	94.27	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-Large + ICDA	Accuracy (%)	92.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-Large + ICDA	Accuracy (%)	87.41	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-Large + ICDA	Accuracy (%)	82.45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MIDAS	Accuarcy	85.02	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	General SLU Model w/ Profile	Accuracy	0.85	—	Unverified