Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generating High-Quality and Informative Conversation Responses with
  Sequence-to-Sequence Models   Sequence-to-sequence models have been applied to the conversation response
generation problem where the source sequence is the conversation history and
the target sequence is the response. Unlike translation, conversation
responding is inherently creative. The generation of long, informative,
coherent, and diverse responses remains a hard task. In this work, we focus on
the single turn setting. We add self-attention to the decoder to maintain
coherence in longer responses, and we propose a practical approach, called the
glimpse-model, for scaling to large datasets. We introduce a stochastic
beam-search algorithm with segment-by-segment reranking which lets us inject
diversity earlier in the generation process. We trained on a combined data set
of over 2.3B conversation messages mined from the web. In human evaluation
studies, our method produces longer responses overall, with a higher proportion
rated as acceptable and excellent as length increases, compared to baseline
sequence-to-sequence models with explicit length-promotion. A back-off strategy
produces better responses overall, in the full spectrum of lengths.

26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
19
The categories of this paper are: eess
17
The categories of this paper are: q-fin
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
34
The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas