Chatbot
79 papers with code • 0 benchmarks • 5 datasets
Chatbot or conversational AI is a language model designed and implemented to have conversations with humans.
Source: Open Data Chatbot
Benchmarks
These leaderboards are used to track progress in Chatbot
Libraries
Use these libraries to find Chatbot models and implementations
Blended Skill Talk
Taiga Corpus
Most implemented papers
End-to-End Task-Completion Neural Dialogue Systems
One of the major drawbacks of modularized task-completion dialogue systems is that each module is trained individually, which presents several challenges.
Visual Dialog
We introduce the task of Visual Dialog, which requires an AI agent to hold a meaningful dialog with humans in natural, conversational language about visual content.
Deep Reinforcement Learning for Dialogue Generation
liuyuemaicha/Deep-Reinforcement-Learning-for-Dialogue-Generation-in-tensorflow
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EMNLP 2016
Recent neural models of dialogue generation offer great promise for generating responses for conversational agents, but tend to be shortsighted, predicting utterances one at a time while ignoring their influence on future outcomes.
Recipes for building an open-domain chatbot
facebookresearch/ParlAI
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EACL 2021
Building open-domain chatbots is a challenging area for machine learning research.
Subword Semantic Hashing for Intent Classification on Small Datasets
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.
Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network
Human generates responses relying on semantic and functional dependencies, including coreference relation, among dialogue elements and their context.
CAiRE: An Empathetic Neural Chatbot
In this paper, we present an end-to-end empathetic conversation agent CAiRE.
Towards a Human-like Open-Domain Chatbot
We present Meena, a multi-turn open-domain chatbot trained end-to-end on data mined and filtered from public domain social media conversations.
Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus
bangliu/ACS-QG
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In this paper, we propose Answer-Clue-Style-aware Question Generation (ACS-QG), which aims at automatically generating high-quality and diverse question-answer pairs from unlabeled text corpus at scale by imitating the way a human asks questions.
HHH: An Online Medical Chatbot System based on Knowledge Graph and Hierarchical Bi-Directional Attention
14H034160212/HHH-An-Online-Question-Answering-System-for-Medical-Questions
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Proceedings of the Australasian Computer Science Week Multi-conference (ACSW 2020) 2020
This paper proposes a chatbot framework that adopts a hybrid model which consists of a knowledge graph and a text similarity model.
