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 201–225 of 330 papers

Title	Date	Tasks	Status	Hype
Wizard of Search Engine: Access to Information Through Conversations with Search Engines	May 18, 2021	Intent DetectionKeyphrase Extraction	CodeCode Available	1
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding	May 15, 2021	intent-classificationIntent Classification	CodeCode Available	0
OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language Attack	May 12, 2021	intent-classificationIntent Classification	CodeCode Available	1
Coupling Intent and Action for Pedestrian Crossing Behavior Prediction	May 10, 2021	Action DetectionAutonomous Vehicles	CodeCode Available	1
Continuous representations of intents for dialogue systems	May 8, 2021	Intent DetectionZero-Shot Learning	—Unverified	0
Pseudo Siamese Network for Few-shot Intent Generation	May 3, 2021	Intent DetectionObject	—Unverified	0
Multilingual and Cross-Lingual Intent Detection from Spoken Data	Apr 17, 2021	Few-Shot LearningIntent Detection	—Unverified	0
Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding	Apr 13, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Intent Detection and Slot Filling for Vietnamese	Apr 5, 2021	Intent Classification and Slot FillingIntent Detection	CodeCode Available	1
Automatic Intent-Slot Induction for Dialogue Systems	Mar 16, 2021	Intent Detectionslot-filling	—Unverified	0
Joint Intent Detection And Slot Filling Based on Continual Learning Model	Feb 22, 2021	Continual LearningIntent Detection	—Unverified	0
Darknet Traffic Big-Data Analysis and Network Management to Real-Time Automating the Malicious Intent Detection Process by a Weight Agnostic Neural Networks Framework	Feb 16, 2021	Cloud ComputingIntent Detection	—Unverified	0
Joint Intent Detection and Slot Filling with Wheel-Graph Attention Networks	Feb 9, 2021	Graph AttentionIntent Detection	—Unverified	0
Generalized Zero-shot Intent Detection via Commonsense Knowledge	Feb 4, 2021	Intent Detection	—Unverified	0
Confusion2vec 2.0: Enriching Ambiguous Spoken Language Representations with Subwords	Feb 3, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	0
A Neural Few-Shot Text Classification Reality Check	Jan 28, 2021	ClassificationFew-Shot Text Classification	CodeCode Available	1
A survey of joint intent detection and slot-filling models in natural language understanding	Jan 20, 2021	ClassificationGeneral Classification	—Unverified	0
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection	Jan 11, 2021	intent-classificationIntent Classification	—Unverified	0
Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling	Dec 21, 2020	Intent DetectionMulti-Task Learning	—Unverified	0
T-WaveNet: Tree-Structured Wavelet Neural Network for Sensor-Based Time Series Analysis	Dec 10, 2020	Activity RecognitionBrain Computer Interface	—Unverified	0
Few-shot Pseudo-Labeling for Intent Detection	Dec 8, 2020	ClusteringIntent Detection	CodeCode Available	0
Benchmarking Commercial Intent Detection Services with Practice-Driven Evaluations	Dec 7, 2020	BenchmarkingGoal-Oriented Dialog	CodeCode Available	0
Learning Class-Transductive Intent Representations for Zero-shot Intent Detection	Dec 3, 2020	Intent DetectionMulti-Task Learning	CodeCode Available	1
Unified Multi Intent Order and Slot Prediction using Selective Learning Propagation	Dec 1, 2020	Intent DetectionNatural Language Understanding	—Unverified	0
Federated Learning for Spoken Language Understanding	Dec 1, 2020	Federated LearningIntent Detection	—Unverified	0

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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	Accuracy	97.76	—	Unverified
8	SF-ID (BLSTM) network	Accuracy	97.76	—	Unverified
9	JointBERT-CAE	Accuracy	97.5	—	Unverified
10	Joint 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	Co-guiding Net	Accuracy	97.7	—	Unverified
5	TFMN	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	UGEN	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	RoBERTa (PACL)	Accuracy	79.1	—	Unverified
8	Co-guiding Net	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