Dialogue Generation
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Dialogue generation is the task of "understanding" natural language inputs - within natural language processing in order to produce output. The systems are usually intended for conversing with humans, for instance back and forth dialogue with a conversation agent like a chatbot. Some example benchmarks for this task (see others such as Natural Language Understanding) include FusedChat and Ubuntu DIalogue Corpus (UDC). Models can be evaluated via metrics such as BLEU, ROUGE, and METEOR albeit with challenges in terms of weak correlation with human judgement, that may be addressed by new ones like UnSupervised and Reference-free (USR) and Metric for automatic Unreferenced dialog evaluation (MaUde).
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ruckbreasoning/glm-dialog
공식 코드GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation
https://github.com/russellliu0/rad
공식 코드https://github.com/scutcyr/CPED
공식 코드CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI
https://github.com/seungheondoh/lp-music-dialog
공식 코드Music Discovery Dialogue Generation Using Human Intent Analysis and Large Language Models
https://github.com/shaojiejiang/ct-loss
공식 코드A Simple Contrastive Learning Objective for Alleviating Neural Text Degeneration
https://github.com/shiquanyang/ns-dial
공식 코드An Interpretable Neuro-Symbolic Reasoning Framework for Task-Oriented Dialogue Generation
https://github.com/shubhamagarwal92/mmd
공식 코드Improving Context Modelling in Multimodal Dialogue Generation
https://github.com/siat-nlp/TransDG
공식 코드Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering
https://github.com/silverriver/mmchat
공식 코드https://github.com/simon-p-j-r/medref
공식 코드Enhancing Medical Dialogue Generation through Knowledge Refinement and Dynamic Prompt Adjustment
https://github.com/skywalker023/focused-empathy
공식 코드Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes
https://github.com/skywalker023/pragmatic-consistency
공식 코드https://github.com/skywalker023/prosocial-dialog
공식 코드ProsocialDialog: A Prosocial Backbone for Conversational Agents
https://github.com/skywalker023/sodaverse
공식 코드SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization
https://github.com/snakeztc/NeuralDialog-CVAE
공식 코드https://github.com/snakeztc/NeuralDialog-LAED
공식 코드Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation
https://github.com/snakeztc/NeuralDialog-LaRL
공식 코드https://github.com/snakeztc/NeuralDialog-ZSDG
공식 코드Zero-Shot Dialog Generation with Cross-Domain Latent Actions
https://github.com/snakeztc/SimDial
공식 코드Zero-Shot Dialog Generation with Cross-Domain Latent Actions
https://github.com/songhaoyu/BoB
공식 코드BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data
https://github.com/songhaoyu/RCDG
공식 코드Generating Persona Consistent Dialogues by Exploiting Natural Language Inference
https://github.com/stevenzhb/cadge
공식 코드CADGE: Context-Aware Dialogue Generation Enhanced with Graph-Structured Knowledge Aggregation
https://github.com/suvodipdey/bok
공식 코드BoK: Introducing Bag-of-Keywords Loss for Interpretable Dialogue Response Generation
https://github.com/suvodipdey/dialogen
공식 코드DialoGen: Generalized Long-Range Context Representation for Dialogue Systems
https://github.com/synlp/chimed-gpt
공식 코드https://github.com/tangg555/meddialog
공식 코드https://github.com/tangg555/sabart
공식 코드Enhancing Dialogue Generation via Dynamic Graph Knowledge Aggregation
https://github.com/teigenzhang/escot
공식 코드ESCoT: Towards Interpretable Emotional Support Dialogue Systems
https://github.com/telepathylabsai/OpenDF
공식 코드https://github.com/thu-coai/CDial-GPT
공식 코드https://github.com/thu-coai/augesc
공식 코드AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation
https://github.com/thu-coai/characterglm-6b
공식 코드CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models
https://github.com/tigerwww-git/rt-kgd
공식 코드RT-KGD: Relation Transition Aware Knowledge-Grounded Dialogue Generation
https://github.com/tomyoung903/fusedchat
공식 코드Fusing task-oriented and open-domain dialogues in conversational agents
https://github.com/toyhom/clv
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.