Intent Classification
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Intent Classification is the task of correctly labeling a natural language utterance from a predetermined set of intents
Source: Multi-Layer Ensembling Techniques for Multilingual Intent Classification
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/193746/jsrsl
공식 코드Joint Automatic Speech Recognition And Structure Learning For Better Speech Understanding
https://github.com/AshishMittal/RMLIntent
공식 코드Representation based meta-learning for few-shot spoken intent recognition
https://github.com/CoraJung/flexible-input-slu
공식 코드Speak or Chat with Me: End-to-End Spoken Language Understanding System with Flexible Inputs
https://github.com/DominiqueMercier/ImpactCite
공식 코드ImpactCite: An XLNet-based method for Citation Impact Analysis
https://github.com/Gorov/DiverseFewShot_Amazon
공식 코드https://github.com/Hossam-Mohammed-tech/Intent_Classification_OOS
공식 코드Improved Out-of-Scope Intent Classification with Dual Encoding and Threshold-based Re-Classification
https://github.com/IIP-Sogang/speech-pooling-benchmark
공식 코드Unsupervised Speech Representation Pooling Using Vector Quantization
https://github.com/Jiang-Yidi/TransformerDistillation-SLU
공식 코드Knowledge Distillation from BERT Transformer to Speech Transformer for Intent Classification
https://github.com/Kaleidophon/deep-significance
공식 코드https://github.com/NVIDIA/NeMo
공식 코드Efficient Sequence Transduction by Jointly Predicting Tokens and Durations
https://github.com/Observeai-Research/Phoneme-BERT
공식 코드Phoneme-BERT: Joint Language Modelling of Phoneme Sequence and ASR Transcript
https://github.com/Perevalov/intent_classifier
공식 코드https://github.com/UKPLab/llm_classifier
공식 코드https://github.com/abderrahmanskiredj/DarijaBanking
공식 코드https://github.com/ago3/plead
공식 코드Explainable Abuse Detection as Intent Classification and Slot Filling
https://github.com/akshittyagi/intclass
공식 코드Fast Intent Classification for Spoken Language Understanding
https://github.com/ala-na/media_benchmark_intent_annotations
공식 코드New Semantic Task for the French Spoken Language Understanding MEDIA Benchmark
https://github.com/alexa/dialoglue
공식 코드https://github.com/alexa/massive
공식 코드https://github.com/algoprog/syntod
공식 코드Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language Models
https://github.com/allenai/scicite
공식 코드Structural Scaffolds for Citation Intent Classification in Scientific Publications
https://github.com/amazon-research/dse
공식 코드Learning Dialogue Representations from Consecutive Utterances
https://github.com/amazon-research/multiatis
공식 코드End-to-End Slot Alignment and Recognition for Cross-Lingual NLU
https://github.com/amazon-research/real-world-noisy-benchmarks-for-natural-language-understanding
공식 코드https://github.com/amazon-research/stil-mbart-multiatis
공식 코드https://github.com/amazon-science/intent-aware-encoder
공식 코드Pre-training Intent-Aware Encoders for Zero- and Few-Shot Intent Classification
https://github.com/asappresearch/dynamic-classification
공식 코드https://github.com/asappresearch/interactive-classification
공식 코드https://github.com/avisheklahiri/citeprompt
공식 코드CitePrompt: Using Prompts to Identify Citation Intent in Scientific Papers
https://github.com/awslabs/pptod
공식 코드Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System
https://github.com/bowang-rw-02/scl-one-for-four
공식 코드One Stone, Four Birds: A Comprehensive Solution for QA System Using Supervised Contrastive Learning
https://github.com/briansidp/espnet
공식 코드End-to-end Spoken Language Understanding with Tree-constrained Pointer Generator
https://github.com/caisa-lab/llms-real-world-noise-robustness
공식 코드Exploring Robustness of Multilingual LLMs on Real-World Noisy Data
https://github.com/cbluebenchmark/cblue
공식 코드CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
https://github.com/clinc/oos-eval
공식 코드An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.