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 51–75 of 330 papers

Title	Date	Tasks	Status	Hype
A Neural Few-Shot Text Classification Reality Check	Jan 28, 2021	ClassificationFew-Shot Text Classification	CodeCode Available	1
MCENET: Multi-Context Encoder Network for Homogeneous Agent Trajectory Prediction in Mixed Traffic	Feb 14, 2020	Autonomous DrivingIntent Detection	CodeCode Available	1
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection	Jun 8, 2021	intent-classificationIntent Classification	CodeCode Available	1
A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding	Nov 8, 2022	Intent DetectionSemantic Frame Parsing	—Unverified	0
A Pointer Network-based Approach for Joint Extraction and Detection of Multi-Label Multi-Class Intents	Oct 29, 2024	Intent DetectionTask-Oriented Dialogue Systems	—Unverified	0
Demonstration of interactive teaching for end-to-end dialog control with hybrid code networks	Aug 1, 2017	Dialog LearningEntity Extraction using GAN	—Unverified	0
Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning	Dec 11, 2024	ClassificationDecoder	—Unverified	0
Benchmarking Adaptive Intelligence and Computer Vision on Human-Robot Collaboration	Sep 30, 2024	BenchmarkingIntent Detection	—Unverified	0
Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection	Feb 27, 2024	Intent DetectionTransfer Learning	—Unverified	0
Benben: A Chinese Intelligent Conversational Robot	Jul 1, 2017	Chinese Word SegmentationDependency Parsing	—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
Bringing Semantic Structures to User Intent Detection in Online Medical Queries	Oct 22, 2017	Intent DetectionMulti-Task Learning	—Unverified	0
Density-Based Dynamic Curriculum Learning for Intent Detection	Aug 24, 2021	Intent Detection	—Unverified	0
Balanced Joint Adversarial Training for Robust Intent Detection and Slot Filling	Dec 1, 2020	Intent Detectionslot-filling	—Unverified	0
An Interdisciplinary Review of Commonsense Reasoning and Intent Detection	Jun 16, 2025	Intent DetectionNatural Language Understanding	—Unverified	0
A Dual-Attention Hierarchical Recurrent Neural Network for Dialogue Act Classification	Oct 22, 2018	ClassificationDialogue Act Classification	—Unverified	0
Automatic Intent-Slot Induction for Dialogue Systems	Mar 16, 2021	Intent Detectionslot-filling	—Unverified	0
Automatic driving lane change safety prediction model based on LSTM	Feb 28, 2024	Autonomous DrivingAutonomous Vehicles	—Unverified	0
Deep F-measure Maximization for End-to-End Speech Understanding	Aug 8, 2020	FairnessIntent Detection	—Unverified	0
Almawave-SLU: A new dataset for SLU in Italian	Jul 17, 2019	Intent DetectionQuestion Answering	—Unverified	0
Lane Change Intention Recognition and Vehicle Status Prediction for Autonomous Vehicles	Apr 25, 2023	Autonomous VehiclesIntent Detection	—Unverified	0
Audio-Visual Understanding of Passenger Intents for In-Cabin Conversational Agents	Jul 8, 2020	Dialogue UnderstandingIntent Detection	—Unverified	0
A Two-Stage Prediction-Aware Contrastive Learning Framework for Multi-Intent NLU	May 5, 2024	Contrastive LearningData Augmentation	—Unverified	0
A deep learning approach for understanding natural language commands for mobile service robots	Jul 9, 2018	Action DetectionIntent 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

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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