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 51100 of 330 papers

TitleStatusHype
A Neural Few-Shot Text Classification Reality CheckCode1
MISCA: A Joint Model for Multiple Intent Detection and Slot Filling with Intent-Slot Co-AttentionCode1
JPIS: A Joint Model for Profile-based Intent Detection and Slot Filling with Slot-to-Intent AttentionCode1
A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding0
A Pointer Network-based Approach for Joint Extraction and Detection of Multi-Label Multi-Class Intents0
Experimental Evaluation of Machine Learning Models for Goal-oriented Customer Service Chatbot with Pipeline Architecture0
Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning0
Benchmarking Adaptive Intelligence and Computer Vision on Human-Robot Collaboration0
Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection0
Benben: A Chinese Intelligent Conversational Robot0
Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding0
Bringing Semantic Structures to User Intent Detection in Online Medical Queries0
Expanding the Text Classification Toolbox with Cross-Lingual Embeddings0
Explainable and Accurate Natural Language Understanding for Voice Assistants and Beyond0
Balanced Joint Adversarial Training for Robust Intent Detection and Slot Filling0
An Interdisciplinary Review of Commonsense Reasoning and Intent Detection0
A Dual-Attention Hierarchical Recurrent Neural Network for Dialogue Act Classification0
Automatic Intent-Slot Induction for Dialogue Systems0
Automatic driving lane change safety prediction model based on LSTM0
Estimating Soft Labels for Out-of-Domain Intent Detection0
Almawave-SLU: A new dataset for SLU in Italian0
Lane Change Intention Recognition and Vehicle Status Prediction for Autonomous Vehicles0
Enriched Pre-trained Transformers for Joint Slot Filling and Intent Detection0
Audio-Visual Understanding of Passenger Intents for In-Cabin Conversational Agents0
A Two-Stage Prediction-Aware Contrastive Learning Framework for Multi-Intent NLU0
A deep learning approach for understanding natural language commands for mobile service robots0
Entity Aware Syntax Tree Based Data Augmentation for Natural Language Understanding0
Evaluating Pixel Language Models on Non-Standardized Languages0
Explainable Slot Type Attentions to Improve Joint Intent Detection and Slot Filling0
EmotionQueen: A Benchmark for Evaluating Empathy of Large Language Models0
Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling0
Darknet Traffic Big-Data Analysis and Network Management to Real-Time Automating the Malicious Intent Detection Process by a Weight Agnostic Neural Networks Framework0
A Transformer-based Threshold-Free Framework for Multi-Intent NLU0
A Joint and Domain-Adaptive Approach to Spoken Language Understanding0
Embedding Grammars0
CroPrompt: Cross-task Interactive Prompting for Zero-shot Spoken Language Understanding0
A survey of joint intent detection and slot-filling models in natural language understanding0
Cost-Based Goal Recognition Meets Deep Learning0
ConvFiT: Conversational Fine-Tuning of Pretrained Language Models0
Deep F-measure Maximization for End-to-End Speech Understanding0
A Streaming End-to-End Framework For Spoken Language Understanding0
Continuous representations of intents for dialogue systems0
Interpretation of the Intent Detection Problem as Dynamics in a Low-dimensional Space0
Demonstration of interactive teaching for end-to-end dialog control with hybrid code networks0
Density-Based Dynamic Curriculum Learning for Intent Detection0
Designing deep neural networks for driver intention recognition0
Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence0
DFKI Cabin Simulator: A Test Platform for Visual In-Cabin Monitoring Functions0
Continual Learning with Dirichlet Generative-based Rehearsal0
A Graph-to-Sequence Model for Joint Intent Detection and Slot Filling in Task-Oriented Dialogue Systems0
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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