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Intent Classification

16 papers with code · Natural Language Processing

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

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Greatest papers with code

Benchmarking Natural Language Understanding Services for building Conversational Agents

13 Mar 2019RasaHQ/rasa

We have recently seen the emergence of several publicly available Natural Language Understanding (NLU) toolkits, which map user utterances to structured, but more abstract, Dialogue Act (DA) or Intent specifications, while making this process accessible to the lay developer.

INTENT CLASSIFICATION NATURAL LANGUAGE UNDERSTANDING

The First Evaluation of Chinese Human-Computer Dialogue Technology

29 Sep 2017InsaneLife/ChineseNLPCorpus

In this paper, we introduce the first evaluation of Chinese human-computer dialogue technology.

INTENT CLASSIFICATION

Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling

6 Sep 2016DSKSD/RNN-for-Joint-NLU

Attention-based encoder-decoder neural network models have recently shown promising results in machine translation and speech recognition.

INTENT CLASSIFICATION INTENT DETECTION SLOT FILLING

BERT for Joint Intent Classification and Slot Filling

28 Feb 2019monologg/JointBERT

Intent classification and slot filling are two essential tasks for natural language understanding.

INTENT CLASSIFICATION NATURAL LANGUAGE UNDERSTANDING SLOT FILLING

Subword Semantic Hashing for Intent Classification on Small Datasets

16 Oct 2018kumar-shridhar/Know-Your-Intent

In this paper, we introduce the use of Semantic Hashing as embedding for the task of Intent Classification and achieve state-of-the-art performance on three frequently used benchmarks.

CHATBOT INTENT CLASSIFICATION TEXT CLASSIFICATION WORD EMBEDDINGS

ConveRT: Efficient and Accurate Conversational Representations from Transformers

9 Nov 2019golsun/DialogRPT

General-purpose pretrained sentence encoders such as BERT are not ideal for real-world conversational AI applications; they are computationally heavy, slow, and expensive to train.

CONVERSATIONAL RESPONSE SELECTION INTENT CLASSIFICATION QUANTIZATION

An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction

IJCNLP 2019 clinc/oos-eval

We find that while the classifiers perform well on in-scope intent classification, they struggle to identify out-of-scope queries.

INTENT CLASSIFICATION TEXT CLASSIFICATION

Structural Scaffolds for Citation Intent Classification in Scientific Publications

NAACL 2019 allenai/scicite

Identifying the intent of a citation in scientific papers (e. g., background information, use of methods, comparing results) is critical for machine reading of individual publications and automated analysis of the scientific literature.

CITATION INTENT CLASSIFICATION INTENT CLASSIFICATION READING COMPREHENSION SENTENCE CLASSIFICATION

Submodular Optimization-based Diverse Paraphrasing and its Effectiveness in Data Augmentation

NAACL 2019 malllabiisc/DiPS

Inducing diversity in the task of paraphrasing is an important problem in NLP with applications in data augmentation and conversational agents.

DATA AUGMENTATION INTENT CLASSIFICATION