SOTAVerified

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

Showing 201250 of 330 papers

TitleStatusHype
Wizard of Search Engine: Access to Information Through Conversations with Search EnginesCode1
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language UnderstandingCode0
OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language AttackCode1
Coupling Intent and Action for Pedestrian Crossing Behavior PredictionCode1
Continuous representations of intents for dialogue systems0
Pseudo Siamese Network for Few-shot Intent Generation0
Multilingual and Cross-Lingual Intent Detection from Spoken Data0
Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding0
Intent Detection and Slot Filling for VietnameseCode1
Automatic Intent-Slot Induction for Dialogue Systems0
Joint Intent Detection And Slot Filling Based on Continual Learning Model0
Darknet Traffic Big-Data Analysis and Network Management to Real-Time Automating the Malicious Intent Detection Process by a Weight Agnostic Neural Networks Framework0
Joint Intent Detection and Slot Filling with Wheel-Graph Attention Networks0
Generalized Zero-shot Intent Detection via Commonsense Knowledge0
Confusion2vec 2.0: Enriching Ambiguous Spoken Language Representations with SubwordsCode0
A Neural Few-Shot Text Classification Reality CheckCode1
A survey of joint intent detection and slot-filling models in natural language understanding0
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain DetectionCode0
Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling0
T-WaveNet: Tree-Structured Wavelet Neural Network for Sensor-Based Time Series Analysis0
Few-shot Pseudo-Labeling for Intent DetectionCode0
Benchmarking Commercial Intent Detection Services with Practice-Driven EvaluationsCode0
Learning Class-Transductive Intent Representations for Zero-shot Intent DetectionCode1
Unified Multi Intent Order and Slot Prediction using Selective Learning Propagation0
Federated Learning for Spoken Language Understanding0
Balanced Joint Adversarial Training for Robust Intent Detection and Slot Filling0
Syntactic Graph Convolutional Network for Spoken Language Understanding0
Joint Intent Detection and Entity Linking on Spatial Domain Queries0
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language InferenceCode1
RiSAWOZ: A Large-Scale Multi-Domain Wizard-of-Oz Dataset with Rich Semantic Annotations for Task-Oriented Dialogue ModelingCode1
HPERL: 3D Human Pose Estimation from RGB and LiDARCode0
Few-shot Learning for Multi-label Intent Detection0
Injecting Word Information with Multi-Level Word Adapter for Chinese Spoken Language UnderstandingCode1
A Co-Interactive Transformer for Joint Slot Filling and Intent DetectionCode1
Rank and run-time aware compression of NLP Applications0
Dynamic Semantic Matching and Aggregation Network for Few-shot Intent DetectionCode0
SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot FillingCode1
OpenUE: An Open Toolkit of Universal Extraction from TextCode1
HINT3: Raising the bar for Intent Detection in the WildCode1
PIN: A Novel Parallel Interactive Network for Spoken Language Understanding0
Composed Variational Natural Language Generation for Few-shot Intents0
Intent Detection with WikiHowCode0
User Intention Recognition and Requirement Elicitation Method for Conversational AI Services0
Spending Money Wisely: Online Electronic Coupon Allocation based on Real-Time User Intent Detection0
Resolving Intent Ambiguities by Retrieving Discriminative Clarifying Questions0
Deep F-measure Maximization for End-to-End Speech Understanding0
Privacy Guarantees for De-identifying Text TransformationsCode0
Audio-Visual Understanding of Passenger Intents for In-Cabin Conversational Agents0
Learning Spoken Language Representations with Neural Lattice Language ModelingCode1
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent ClassificationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Bi-model with decoderAccuracy98.99Unverified
2Transformer-CapsuleAccuracy98.89Unverified
3Attention Encoder-Decoder NNAccuracy98.43Unverified
4Joint model with recurrent slot label contextAccuracy98.4Unverified
5CTRANAccuracy98.07Unverified
6Joint BERT + CRFAccuracy97.9Unverified
7SF-IDAccuracy97.76Unverified
8SF-ID (BLSTM) networkAccuracy97.76Unverified
9JointBERT-CAEAccuracy97.5Unverified
10Joint BERTAccuracy97.5Unverified
#ModelMetricClaimedVerifiedStatus
1SSRANAccuracy98.4Unverified
2BiSLUAccuracy97.8Unverified
3DGIFAccuracy97.8Unverified
4Co-guiding NetAccuracy97.7Unverified
5TFMNAccuracy97.7Unverified
6TFMN (PACL)Accuracy97.4Unverified
7MISCAAccuracy97.3Unverified
8Uni-MISAccuracy97.2Unverified
9SLIMAccuracy97.2Unverified
10UGENAccuracy96.9Unverified
#ModelMetricClaimedVerifiedStatus
1DGIFAccuracy83.3Unverified
2UGENAccuracy83Unverified
3TFMN (PACL)Accuracy82.9Unverified
4SLIM (PACL)Accuracy81.9Unverified
5BiSLUAccuracy81.5Unverified
6TFMNAccuracy79.8Unverified
7RoBERTa (PACL)Accuracy79.1Unverified
8Co-guiding NetAccuracy79.1Unverified
9Uni-MISAccuracy78.5Unverified
10SLIMAccuracy78.3Unverified
#ModelMetricClaimedVerifiedStatus
1CTRANAccuracy99.42Unverified
2Stack-Propagation (+BERT)Accuracy99Unverified
3JointBERT-CAEAccuracy98.3Unverified
4AGIFAccuracy98.1Unverified
5LIDSNetAccuracy98Unverified
6Stack-PropagationAccuracy98Unverified
7SF-IDAccuracy97.43Unverified
8SF-ID (BLSTM) networkAccuracy97.43Unverified
9Capsule-NLUAccuracy97.3Unverified
10Slot-Gated BLSTM with AttensionAccuracy97Unverified
#ModelMetricClaimedVerifiedStatus
1plain-LSTMF10.89Unverified
2linear-NgramsF10.87Unverified
3glove-LSTMF10.86Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-Large + ICDAAccuracy (%)94.42Unverified
2OCaTS (kNN-GPT-4)Accuracy (%)82.7Unverified
#ModelMetricClaimedVerifiedStatus
1JointBERT-CAEIntent Accuracy97.7Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-Large + ICDAAccuracy (%)89.79Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-Large + ICDAAccuracy (%)84.01Unverified
#ModelMetricClaimedVerifiedStatus
1CM-NetAcc94.56Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-Large + ICDAAccuracy (%)97.12Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-Large + ICDAAccuracy (%)94.84Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-Large + ICDAAccuracy (%)92.62Unverified
#ModelMetricClaimedVerifiedStatus
1MIDASAccuracy94.27Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-Large + ICDAAccuracy (%)92.57Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-Large + ICDAAccuracy (%)87.41Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-Large + ICDAAccuracy (%)82.45Unverified
#ModelMetricClaimedVerifiedStatus
1MIDASAccuarcy85.02Unverified
#ModelMetricClaimedVerifiedStatus
1General SLU Model w/ ProfileAccuracy0.85Unverified