Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Self-Guiding Multimodal LSTM - when we do not have a perfect training
  dataset for image captioning   In this paper, a self-guiding multimodal LSTM (sg-LSTM) image captioning
model is proposed to handle uncontrolled imbalanced real-world image-sentence
dataset. We collect FlickrNYC dataset from Flickr as our testbed with 306,165
images and the original text descriptions uploaded by the users are utilized as
the ground truth for training. Descriptions in FlickrNYC dataset vary
dramatically ranging from short term-descriptions to long
paragraph-descriptions and can describe any visual aspects, or even refer to
objects that are not depicted. To deal with the imbalanced and noisy situation
and to fully explore the dataset itself, we propose a novel guiding textual
feature extracted utilizing a multimodal LSTM (m-LSTM) model. Training of
m-LSTM is based on the portion of data in which the image content and the
corresponding descriptions are strongly bonded. Afterwards, during the training
of sg-LSTM on the rest training data, this guiding information serves as
additional input to the network along with the image representations and the
ground-truth descriptions. By integrating these input components into a
multimodal block, we aim to form a training scheme with the textual information
tightly coupled with the image content. The experimental results demonstrate
that the proposed sg-LSTM model outperforms the traditional state-of-the-art
multimodal RNN captioning framework in successfully describing the key
components of the input images.

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The categories of this paper are: eess
24
The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
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The categories of this paper are: mtrl-th
16
The categories of this paper are: stat
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The categories of this paper are: acc-phys
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The categories of this paper are: solv-int
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The categories of this paper are: hep-lat
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The categories of this paper are: quant-ph
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The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
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The categories of this paper are: cond-mat
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The categories of this paper are: patt-sol
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The categories of this paper are: astro-ph
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The categories of this paper are: econ