mlsanityData to 7 Oct 2026

DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation

arXiv 1911.00536 ↗First posted 1 Nov 2019cs.CL cs.LGcited by 842

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Cited by 28 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We present a large, tunable neural conversational response generation model, DialoGPT (dialogue generative pre-trained transformer). Trained on 147M conversation-like exchanges extracted from Reddit comment chains over a period spanning from 2005 through 2017, DialoGPT extends the Hugging Face PyTorch transformer to attain a performance close to human both in terms of automatic and human evaluation in single-turn dialogue settings. We show that conversational systems that leverage DialoGPT generate more relevant, contentful and context-consistent responses than strong baseline systems. The pre-trained model and training pipeline are publicly released to facilitate research into neural response generation and the development of more intelligent open-domain dialogue systems.

Key facts. Cited by 842 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Nov 2019.

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Citing papers per year: 2020: 1; 2021: 176; 2022: 225; 2023: 220; 2024: 108; 2025: 76; 2026: 36.

842 papers.

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38 more
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