Papers › TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
Thomas Wolf, Victor Sanh, Julien Chaumond, Clement Delangue
We introduce a new approach to generative data-driven dialogue systems (e.g. chatbots) called TransferTransfo which is a combination of a Transfer learning based training scheme and a high-capacity Transformer model. Fine-tuning is performed by using a multi-task objective which combines several unsupervised prediction tasks. The resulting fine-tuned model shows strong improvements over the current state-of-the-art end-to-end conversational models like memory augmented seq2seq and information-retrieval models. On the privately held PERSONA-CHAT dataset of the Conversational Intelligence Challenge 2, this approach obtains a new state-of-the-art, with respective perplexity, Hits@1 and F1 metrics of 16.28 (45 % absolute improvement), 80.7 (46 % absolute improvement) and 19.5 (20 % absolute improvement).
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Code
Syntology Ran 8 of 26 code samples harvested from 8 repositories linked to this paper; 18 have no recorded run. Of those that ran: 1 ran · honoured contract; 4 ran · our draft was wrong; 3 ran · fixture could not drive it.
By repository: community (archive-listed): 25 samples from 8 repositories, 8 ran; 1 identical to code first harvested elsewhere. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.
23 repositories listed; official and paper-mentioned ones first.
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Code Syntology ran Syntology
26 samples harvested; 8 ran; 1 honoured the contract we drafted; 18 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Dialogue Generation | Persona-Chat | TransferTransfo | Avg F1 | 19.09 | #3 of 6 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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