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 101150 of 330 papers

TitleStatusHype
A Unified Framework for Multi-intent Spoken Language Understanding with promptingCode0
Tri-level Joint Natural Language Understanding for Multi-turn Conversational DatasetsCode0
Multi-grained Label Refinement Network with Dependency Structures for Joint Intent Detection and Slot FillingCode0
Out-of-Scope Intent Detection with Self-Supervision and Discriminative TrainingCode0
Intention Recognition in Real-Time Interactive Navigation MapsCode0
ChatGPT as Data Augmentation for Compositional Generalization: A Case Study in Open Intent DetectionCode0
Intention Recognition of Pedestrians and Cyclists by 2D Pose EstimationCode0
A Weight-aware-based Multi-source Unsupervised Domain Adaptation Method for Human Motion Intention RecognitionCode0
ed-cec: improving rare word recognition using asr postprocessing based on error detection and context-aware error correctionCode0
Effectiveness of Pre-training for Few-shot Intent ClassificationCode0
Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and SylhetiCode0
Few-shot Pseudo-Labeling for Intent DetectionCode0
Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting FrameworkCode0
Intent Detection with WikiHowCode0
Incorporating Instructional Prompts into a Unified Generative Framework for Joint Multiple Intent Detection and Slot FillingCode0
CAE: Mechanism to Diminish the Class Imbalanced in SLU Slot Filling TaskCode0
Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case StudyCode0
Enhancing Joint Multiple Intent Detection and Slot Filling with Global Intent-Slot Co-occurrenceCode0
Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent DetectionCode0
HIT-SCIR at MMNLU-22: Consistency Regularization for Multilingual Spoken Language UnderstandingCode0
Deep Unknown Intent Detection with Margin LossCode0
HPERL: 3D Human Pose Estimation from RGB and LiDARCode0
Integrating Text and Image: Determining Multimodal Document Intent in Instagram PostsCode0
Joint Slot Filling and Intent Detection via Capsule Neural NetworksCode0
Explainable and Accurate Natural Language Understanding for Voice Assistants and Beyond0
Experimental Evaluation of Machine Learning Models for Goal-oriented Customer Service Chatbot with Pipeline Architecture0
Bringing Semantic Structures to User Intent Detection in Online Medical Queries0
Expanding the Text Classification Toolbox with Cross-Lingual Embeddings0
Evaluating Pixel Language Models on Non-Standardized Languages0
Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding0
Estimating Soft Labels for Out-of-Domain Intent Detection0
Entity Aware Syntax Tree Based Data Augmentation for Natural Language Understanding0
Enriched Pre-trained Transformers for Joint Slot Filling and Intent Detection0
Enhancing Slot Tagging with Intent Features for Task Oriented Natural Language Understanding using BERT0
Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection0
A Pointer Network-based Approach for Joint Extraction and Detection of Multi-Label Multi-Class Intents0
A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding0
Enhanced Urdu Intent Detection with Large Language Models and Prototype-Informed Predictive Pipelines0
Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling0
EmotionQueen: A Benchmark for Evaluating Empathy of Large Language Models0
Embedding Grammars0
Benchmarking Adaptive Intelligence and Computer Vision on Human-Robot Collaboration0
Benben: A Chinese Intelligent Conversational Robot0
Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning0
dzFinNlp at AraFinNLP: Improving Intent Detection in Financial Conversational Agents0
Balanced Joint Adversarial Training for Robust Intent Detection and Slot Filling0
Diversity-grounded Channel Prototypical Learning for Out-of-Distribution Intent Detection0
Distributionally Robust Semi-Supervised Learning for People-Centric Sensing0
Automatic Intent-Slot Induction for Dialogue Systems0
Automatic driving lane change safety prediction model based on LSTM0
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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