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
BlendX: Complex Multi-Intent Detection with Blended Patterns	Mar 27, 2024	DiversityIntent Detection	CodeCode Available	1
Uni-MIS: United Multiple Intent Spoken Language Understanding via Multi-View Intent-Slot Interaction	Mar 24, 2024	Intent Detectionslot-filling	CodeCode Available	0
RECIPE4U: Student-ChatGPT Interaction Dataset in EFL Writing Education	Mar 13, 2024	Intent DetectionTask-Oriented Dialogue Systems	—Unverified	0
Automatic driving lane change safety prediction model based on LSTM	Feb 28, 2024	Autonomous DrivingAutonomous Vehicles	—Unverified	0
Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection	Feb 27, 2024	Intent DetectionTransfer Learning	—Unverified	0
Intelligent Mode-switching Framework for Teleoperation	Feb 8, 2024	Decision MakingDeep Reinforcement Learning	—Unverified	0
Designing deep neural networks for driver intention recognition	Feb 7, 2024	Intent DetectionNeural Architecture Search	—Unverified	0
SDIF-DA: A Shallow-to-Deep Interaction Framework with Data Augmentation for Multi-modal Intent Detection	Dec 31, 2023	Data AugmentationIntent Detection	CodeCode Available	1
JPIS: A Joint Model for Profile-based Intent Detection and Slot Filling with Slot-to-Intent Attention	Dec 14, 2023	Intent Detectionslot-filling	CodeCode Available	1
ICL Markup: Structuring In-Context Learning using Soft-Token Tags	Dec 12, 2023	In-Context LearningIntent Detection	—Unverified	0
MISCA: A Joint Model for Multiple Intent Detection and Slot Filling with Intent-Slot Co-Attention	Dec 10, 2023	graph constructionIntent Detection	CodeCode Available	1
SQATIN: Supervised Instruction Tuning Meets Question Answering for Improved Dialogue NLU	Nov 16, 2023	Intent DetectionNatural Language Understanding	CodeCode Available	0
Making LLMs Worth Every Penny: Resource-Limited Text Classification in Banking	Nov 10, 2023	Contrastive LearningData Augmentation	—Unverified	0
ArBanking77: Intent Detection Neural Model and a New Dataset in Modern and Dialectical Arabic	Oct 29, 2023	Intent Detection	—Unverified	0
IntenDD: A Unified Contrastive Learning Approach for Intent Detection and Discovery	Oct 25, 2023	Contrastive Learningintent-classification	—Unverified	0
Cache me if you Can: an Online Cost-aware Teacher-Student framework to Reduce the Calls to Large Language Models	Oct 20, 2023	Intent DetectionIntent Recognition	CodeCode Available	1
IntentDial: An Intent Graph based Multi-Turn Dialogue System with Reasoning Path Visualization	Oct 18, 2023	Intent Detection	—Unverified	0
Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti	Oct 17, 2023	Intent Detectionslot-filling	CodeCode Available	0
Key-phrase boosted unsupervised summary generation for FinTech organization	Oct 16, 2023	Intent DetectionSentiment Analysis	—Unverified	0
RSVP: Customer Intent Detection via Agent Response Contrastive and Generative Pre-Training	Oct 15, 2023	Intent DetectionResponse Generation	CodeCode Available	0
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	0
I^2KD-SLU: An Intra-Inter Knowledge Distillation Framework for Zero-Shot Cross-Lingual Spoken Language Understanding	Oct 4, 2023	Intent DetectionKnowledge Distillation	—Unverified	0
Explainable and Accurate Natural Language Understanding for Voice Assistants and Beyond	Sep 25, 2023	General ClassificationIntent Detection	—Unverified	0
ChEDDAR: Student-ChatGPT Dialogue in EFL Writing Education	Sep 23, 2023	Intent DetectionTask-Oriented Dialogue Systems	CodeCode Available	0
Intent Detection at Scale: Tuning a Generic Model using Relevant Intents	Sep 15, 2023	Intent 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 (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