Intent Detection
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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 <span class="description-source">
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/PolyAI-LDN/task-specific-datasets
https://github.com/SJY8460/Uni-MIS
https://github.com/ShawonAshraf/nlu-jointbert-dl2021
https://github.com/SuperBruceJia/EEG-DL
Attention-based Graph ResNet for Motor Intent Detection from Raw EEG signals
https://github.com/Tushar-ml/ED-CEC
https://github.com/ZIZUN/CPFT
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning
https://github.com/ZephyrChenzf/SF-ID-Network-For-NLU
A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling
https://github.com/adlnlp/Midas
MIDAS: Multi-level Intent, Domain, And Slot Knowledge Distillation for Multi-turn NLU
https://github.com/alibaba-damo-academy/spokennlp
https://github.com/amazon-science/intent-aware-encoder
https://github.com/asadovsky/nn
https://github.com/bhchoi/bert-for-joint-ic-sf
https://github.com/bo-ke/cybo/tree/master/tutorials/slu/slot_gated
https://github.com/congyingxia/ZeroShotCapsule
https://github.com/diridiri/ZeroShotCapsule
https://github.com/dsindex/iclassifier
https://github.com/fabon/chatbot-intents
https://github.com/glhr/ood-labelnoise
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
https://github.com/halimasoulb/human-pose-estimation-3d-lidar
https://github.com/joel-huang/zeroshot-capsnet-pytorch
https://github.com/kakaoenterprise/OutFlip
OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language Attack
https://github.com/mangushev/intent_slot
https://github.com/matthew29tang/pid-model
FuSSI-Net: Fusion of Spatio-temporal Skeletons for Intention Prediction Network
https://github.com/monologg/JointBERT
https://github.com/nhhoang96/ZeroShotCapsule-PyTorch-
https://github.com/pengshuang/Joint-Slot-Filling
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling
https://github.com/phuongnm94/JointBERT_CAE
https://github.com/ray075hl/Bi-Model-Intent-And-Slot
A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling
https://github.com/rparkin1/intent_LSTM
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling
https://github.com/silverriver/ood4nlu
Energy-based Unknown Intent Detection with Data Manipulation
https://github.com/smxiao/GISCo
https://github.com/sonos/svc-demographic-bias-assessment
https://github.com/stanislavfort/adversaries_to_ood_detection
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
https://github.com/stanislavfort/exploring_the_limits_of_OOD_detection
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
https://github.com/sxjscience/GluonNLP-Slot-Filling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.