Data to 7 Oct 2026

PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning

arXiv 2006.16779 ↗First posted 30 Jun 2020cs.CLcited by 79

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Abstract (arXiv)

To build a high-quality open-domain chatbot, we introduce the effective training process of PLATO-2 via curriculum learning. There are two stages involved in the learning process. In the first stage, a coarse-grained generation model is trained to learn response generation under the simplified framework of one-to-one mapping. In the second stage, a fine-grained generative model augmented with latent variables and an evaluation model are further trained to generate diverse responses and to select the best response, respectively. PLATO-2 was trained on both Chinese and English data, whose effectiveness and superiority are verified through comprehensive evaluations, achieving new state-of-the-art results.

Key facts. Cited by 79 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jun 2020.

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Citing papers per year: 2021: 19; 2022: 31; 2023: 20; 2024: 7; 2025: 1; 2026: 1.

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2021Pre-Trained Models: Past, Present and Futurecited by 319
2021Curriculum Learning: A Surveycited by 257
2022Pretrained Language Models for Text Generation: A Surveycited by 121
2022Long Time No See! Open-Domain Conversation with Long-Term Persona Memorycited by 107
2023Lift Yourself Up: Retrieval-augmented Text Generation with Self Memorycited by 103
2021Pretrained Language Models for Text Generation: A Surveycited by 95
2021On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmarkcited by 73
2023Rewarding Chatbots for Real-World Engagement with Millions of Userscited by 58
2021Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterancescited by 40
2022InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuningcited by 39
2021PLATO-XL: Exploring the Large-scale Pre-training of Dialogue Generationcited by 37
2022Towards Identifying Social Bias in Dialog Systems: Frame, Datasets, and Benchmarkscited by 36

38 more

2021Preview, Attend and Review: Schema-Aware Curriculum Learning for Multi-Domain Dialog State Trackingcited by 35
2021EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Trainingcited by 34
2023CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Modelscited by 34
2023Opportunities and Challenges in Neural Dialog Tutoringcited by 33
2022EVA2.0: Investigating Open-Domain Chinese Dialogue Systems with Large-Scale Pre-Trainingcited by 31
2021"How Robust r u?": Evaluating Task-Oriented Dialogue Systems on Spoken Conversationscited by 30
2023Ask an Expert: Leveraging Language Models to Improve Strategic Reasoning in Goal-Oriented Dialogue Modelscited by 30
2024Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLMcited by 26
2023A Survey of the Evolution of Language Model-Based Dialogue Systems: Data, Task and Modelscited by 23
2021Amendable Generation for Dialogue State Trackingcited by 21
2023End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directionscited by 17
2021Learning to Select External Knowledge with Multi-Scale Negative Samplingcited by 16
2022Measuring and Improving Semantic Diversity of Dialogue Generationcited by 16
2024Boost Your Human Image Generation Model via Direct Preference Optimizationcited by 16
2021Addressing Inquiries about History: An Efficient and Practical Framework for Evaluating Open-domain Chatbot Consistencycited by 12
2021UniDS: A Unified Dialogue System for Chit-Chat and Task-oriented Dialoguescited by 12
2021TOD-DA: Towards Boosting the Robustness of Task-oriented Dialogue Modeling on Spoken Conversationscited by 11
2023ACCENT: An Automatic Event Commonsense Evaluation Metric for Open-Domain Dialogue Systemscited by 11
2023Think Before You Speak: Cultivating Communication Skills of Large Language Models via Inner Monologuecited by 11
2022CDConv: A Benchmark for Contradiction Detection in Chinese Conversationscited by 10
2024TriSum: Learning Summarization Ability from Large Language Models with Structured Rationalecited by 10
2022PanGu-Bot: Efficient Generative Dialogue Pre-training from Pre-trained Language Modelcited by 9
2022Interactive Evaluation of Dialog Track at DSTC9cited by 9
2024Dynamic Stochastic Decoding Strategy for Open-Domain Dialogue Generationcited by 9
2022Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generationcited by 8
2023CADGE: Context-Aware Dialogue Generation Enhanced with Graph-Structured Knowledge Aggregationcited by 8
2022Link the World: Improving Open-domain Conversation with Dynamic Spatiotemporal-aware Knowledgecited by 6
2023UniMC: A Unified Framework for Long-Term Memory Conversation via Relevance Representation Learningcited by 6
2022Towards Building an Open-Domain Dialogue System Incorporated with Internet Memescited by 5
2022PoKE: Prior Knowledge Enhanced Emotional Support Conversation with Latent Variablecited by 5
2022Towards Diverse, Relevant and Coherent Open-Domain Dialogue Generation via Hybrid Latent Variablescited by 5
2023KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue Generationcited by 5
2022Improving Bot Response Contradiction Detection via Utterance Rewritingcited by 4
2022Towards Efficient Dialogue Pre-training with Transferable and Interpretable Latent Structurecited by 4
2023Task-oriented Document-Grounded Dialog Systems by HLTPR@RWTH for DSTC9 and DSTC10cited by 4
2023Prompt Learning to Mitigate Catastrophic Forgetting in Cross-lingual Transfer for Open-domain Dialogue Generationcited by 4
2024Improving Linguistic Diversity of Large Language Models with Possibility Exploration Fine-Tuningcited by 4
2021Semantic-Enhanced Explainable Finetuning for Open-Domain Dialoguescited by 3

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