Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: TransferTransfo: A Transfer Learning Approach for Neural Network Based
  Conversational Agents   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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The categories of this paper are: cond-mat
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
19
The categories of this paper are: eess
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The categories of this paper are: astro-ph
16
The categories of this paper are: stat
17
The categories of this paper are: q-fin
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The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
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The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn