Feature request -- bbl2bib-va - a bbl2bib using the ArXiv

[pauloney]

This one will convert a BBL record into a BiB record. And is almost
a copy of this program in the CrossRefWare bundle.

bbl2bib.pl - convert 'thebibliography' environment to a bib file

but instead of dispatching in the direction of

    http://www.ams.org/mathscinet-mref

it will send it in the direction of the ArXiv (same as previous script)

    http://export.arxiv.org/api/query?search_query=id:$1

and get the record just like the first script, parsing the XML and writing the BibTeX entry.

There is only ONE essential difference between the two programs: MathSciNet MRef program accepts a a FULL \bibitem BBL record -- the arxiv program does not. So we have to prepaper the query from an unformatted BBL record.

We should divide it in two cases:

1. The record does contain something like the ArXiv number (xxxx.yyyy or xxxx.yyyyy)

Then use the number to do a search on that ID at the arXiv (just like the first script) and write the number in.

2. Nothing looks like an ArXiv ID.

Then we should use some heuristics to separate the record in AUTHOR and TITLE and do a search like the second script.

Here are some examples of BBL records that would be interesting to try:

\bibitem{CMM} A. Cerqueira, C. Matheus and C. G.
Moreira \ Continuity of Hausdorff dimension across
generic dynamical Lagrange and Markov spectra. https://arxiv.org/abs/1602.04649

\bibitem{CMR} A. Cerqueira, C. G. Moreira, S. Roma\~na \ Continuity
of Hausdorff Dimension Across Generic Dynamical Lagrange and Markov
Spectra II. https://arxiv.org/abs/1711.03851

\bibitem{Mat} C. Matheus, \ The Lagrange and Markov spectra
from the dynamical point of view. arxiv:1703.01748

\bibitem{CMM} A. Cerqueira, C. Matheus and C. G.
Moreira \ Continuity of Hausdorff dimension across
generic dynamical Lagrange and Markov spectra.

\bibitem{CMR} A. Cerqueira, C. G. Moreira, S. Roma\~na \ Continuity
of Hausdorff Dimension Across Generic Dynamical Lagrange and Markov
Spectra II

\bibitem{Mat} C. Matheus, \ The Lagrange and Markov spectra
from the dynamical point of view.

This program will not work well straight out, but tuning it for the match verification would be a nice addition

[pauloney]

Ideally this program (after quite some testing) could be integrated into bbl2bib because by itself it would not make much sense -- you would end up with some converted records, but would have to merge the two files by hand.

The likely implementation would be using an option to ask for MR, another for the ArXiv,or both.

[sisrfeng]

So can we search on arxiv now?

[tex-apprentice]

Tha ArXiv has always been searchable. This request is about integrating the ArXiv search to form a BIB record.

[sisrfeng]

My actual purpose is to solve lots of this failure:

Could you give me some guide?
What about using arxiv' s api to get the bib record of each item in bbl?

[tex-apprentice]

Well ... "No unique match found" is your enemy in this kind of search because if you could not decide what record to use, you could not form the Bib-record, period.

In this situation, you should analyze the results of the search (by hand) and see what can be done to provide more data for the search, so it can achieve a unique record.

Good to remember that this is NOT a problem of the ArXiv, the searches at the AMS (and any other DB) suffer from the same problem.

For example, if you do the search:

ti: Swan conductors for p-adic differential modules

you get two matches: arXiv:0705.0031 and arXiv:math/0611835 which are articles number I and number II. This search will always return a non-uniq result.

If instead, you search for:

ti: Swan conductors for p-adic differential modules, I: A local construction

You get a unique match. In fact, just a search for:

ti: Swan conductors for p-adic differential modules, I

get you already a unique match.

[sisrfeng]

Can we make bib2bbl select the most likely match?

[sisrfeng]

Now I can only get about 1% bib items out of the bbl file

[tex-apprentice]

Can we make bib2bbl select the most likely match?

Not with this search that is currently done. It will have to be a more elaborate search with the possibiity of looking at several results and having a strategy to choose "the most likely" whatever this is defined as ...

[tex-apprentice]

Now I can only get about 1% bib items out of the bbl file

That is probably something else, most likely a not proper BBL file. Post the file here, or better, pieces of it and we can look at the issue.

[sisrfeng]

I'm in China, maybe the Great Fire Wall causes the failure?

bbl:
% Generated by IEEEtran.bst, version: 1.13 (2008/09/30)
\begin{thebibliography}{10}
\providecommand{\url}[1]{#1}
\csname url@samestyle\endcsname
\providecommand{\newblock}{\relax}
\providecommand{\bibinfo}[2]{#2}
\providecommand{\BIBentrySTDinterwordspacing}{\spaceskip=0pt\relax}
\providecommand{\BIBentryALTinterwordstretchfactor}{4}
\providecommand{\BIBentryALTinterwordspacing}{\spaceskip=\fontdimen2\font plus
\BIBentryALTinterwordstretchfactor\fontdimen3\font minus
\fontdimen4\font\relax}
\providecommand{\BIBforeignlanguage}[2]{{%
\expandafter\ifx\csname l@#1\endcsname\relax
\typeout{** WARNING: IEEEtran.bst: No hyphenation pattern has been}%
\typeout{** loaded for the language `#1'. Using the pattern for}%
\typeout{** the default language instead.}%
\else
\language=\csname l@#1\endcsname
\fi
#2}}
\providecommand{\BIBdecl}{\relax}
\BIBdecl

\bibitem{Imagenet}
J.~Deng, W.~Dong, R.~Socher, L.-J. Li, K.~Li, and L.~Fei-Fei, ``{ImageNet: A
Large-Scale Hierarchical Image Database},'' in \emph{CVPR}, 2009.

\bibitem{PASCAL}
M.~Everingham, L.VanGool, C.~K.~I. Williams, J.~Winn, and A.~Zisserman, ``The
{PASCAL} visual object classes ({VOC}) challenge,'' \emph{IJCV}, vol.~88,
no.~2, pp. 303--338, Jun. 2010.

\bibitem{SUN}
J.~Xiao, J.~Hays, K.~A. Ehinger, A.~Oliva, and A.~Torralba, ``{SUN} database:
Large-scale scene recognition from abbey to zoo,'' in \emph{CVPR}, 2010.

\bibitem{Dollar2012PAMI}
P.~Doll'ar, C.~Wojek, B.~Schiele, and P.~Perona, ``Pedestrian detection: An
evaluation of the state of the art,'' \emph{PAMI}, vol.~34, 2012.

\bibitem{Hinton}
A.~Krizhevsky, I.~Sutskever, and G.~Hinton, ``{ImageNet} classification with
deep convolutional neural networks,'' in \emph{NIPS}, 2012.

\bibitem{GirshickDDM13}
R.~Girshick, J.~Donahue, T.~Darrell, and J.~Malik, ``Rich feature hierarchies
for accurate object detection and semantic segmentation,'' in \emph{CVPR},
2014.

\bibitem{OverFeat}
P.~Sermanet, D.~Eigen, S.~Zhang, M.~Mathieu, R.~Fergus, and Y.~LeCun,
``{OverFeat}: Integrated recognition, localization and detection using
convolutional networks,'' in \emph{ICLR}, April 2014.

\bibitem{farhadi2009describing}
A.~Farhadi, I.~Endres, D.~Hoiem, and D.~Forsyth, ``Describing objects by their
attributes,'' in \emph{CVPR}, 2009.

\bibitem{Patterson2012SunAttributes}
G.~Patterson and J.~Hays, ``{SUN} attribute database: Discovering, annotating,
and recognizing scene attributes,'' in \emph{CVPR}, 2012.

\bibitem{bourdev2009poselets}
L.~Bourdev and J.~Malik, ``Poselets: Body part detectors trained using {3D}
human pose annotations,'' in \emph{ICCV}, 2009.

\bibitem{NYUDepth}
N.~Silberman, D.~Hoiem, P.~Kohli, and R.~Fergus, ``Indoor segmentation and
support inference from {RGBD} images,'' in \emph{ECCV}, 2012.

\bibitem{Palmer1981}
S.~Palmer, E.~Rosch, and P.~Chase, ``Canonical perspective and the perception
of objects,'' \emph{Attention and performance IX}, vol.~1, p.~4, 1981.

\bibitem{diagnosing}
.~Hoiem, D, Y.~Chodpathumwan, and Q.~Dai, ``Diagnosing error in object
detectors,'' in \emph{ECCV}, 2012.

\bibitem{brostow2009semantic}
G.~Brostow, J.~Fauqueur, and R.~Cipolla, ``Semantic object classes in video: A
high-definition ground truth database,'' \emph{PRL}, vol.~30, no.~2, pp.
88--97, 2009.

\bibitem{LabelMe}
B.~Russell, A.~Torralba, K.~Murphy, and W.~Freeman, ``{LabelMe}: a database and
web-based tool for image annotation,'' \emph{IJCV}, vol.~77, no. 1-3, pp.
157--173, 2008.

\bibitem{bell13opensurfaces}
S.~Bell, P.~Upchurch, N.~Snavely, and K.~Bala, ``{OpenSurfaces}: A richly
annotated catalog of surface appearance,'' \emph{SIGGRAPH}, vol.~32, no.~4,
2013.

\bibitem{ordonez2011im2text}
V.~Ordonez, G.~Kulkarni, and T.~Berg, ``Im2text: Describing images using 1
million captioned photographs.'' in \emph{NIPS}, 2011.

\bibitem{Olga}
J.~Deng, O.~Russakovsky, J.~Krause, M.~Bernstein, A.~Berg, and L.~Fei-Fei,
``Scalable multi-label annotation,'' in \emph{CHI}, 2014.

\bibitem{eccv}
T.~Lin, M.~Maire, S.~Belongie, J.~Hays, P.~Perona, D.~Ramanan, P.~Doll{'a}r,
and C.~L. Zitnick, ``Microsoft {COCO}: Common objects in context,'' in
\emph{ECCV}, 2014.

\bibitem{scharstein2002taxonomy}
D.~Scharstein and R.~Szeliski, ``A taxonomy and evaluation of dense two-frame
stereo correspondence algorithms,'' \emph{IJCV}, vol.~47, no. 1-3, pp. 7--42,
2002.

\bibitem{baker2011database}
S.~Baker, D.~Scharstein, J.~Lewis, S.~Roth, M.~Black, and R.~Szeliski, ``A
database and evaluation methodology for optical flow,'' \emph{IJCV}, vol.~92,
no.~1, pp. 1--31, 2011.

\bibitem{Caltech101}
L.~Fei-Fei, R.~Fergus, and P.~Perona, ``Learning generative visual models from
few training examples: An incremental bayesian approach tested on 101 object
categories,'' in \emph{CVPR Workshop of Generative Model Based Vision
(WGMBV)}, 2004.

\bibitem{Caltech256}
G.~Griffin, A.~Holub, and P.~Perona, ``Caltech-256 object category dataset,''
California Institute of Technology, Tech. Rep. 7694, 2007.

\bibitem{Dalal}
N.~Dalal and B.~Triggs, ``Histograms of oriented gradients for human
detection,'' in \emph{CVPR}, 2005.

\bibitem{mnist}
\BIBentryALTinterwordspacing
Y.~Lecun and C.~Cortes, ``{The MNIST database of handwritten digits},'' 1998.
[Online]. Available: \url{http://yann.lecun.com/exdb/mnist/}
\BIBentrySTDinterwordspacing

\bibitem{nene1996columbia}
S.~A. Nene, S.~K. Nayar, and H.~Murase, ``Columbia object image library
(coil-20),'' Columbia Universty, Tech. Rep., 1996.

\bibitem{krizhevsky2009learning}
A.~Krizhevsky and G.~Hinton, ``Learning multiple layers of features from tiny
images,'' \emph{Computer Science Department, University of Toronto, Tech.
Rep}, 2009.

\bibitem{torralba200880}
A.~Torralba, R.~Fergus, and W.~T. Freeman, ``80 million tiny images: A large
data set for nonparametric object and scene recognition,'' \emph{PAMI},
vol.~30, no.~11, pp. 1958--1970, 2008.

\bibitem{ordonezlarge}
V.~Ordonez, J.~Deng, Y.~Choi, A.~Berg, and T.~Berg, ``From large scale image
categorization to entry-level categories,'' in \emph{ICCV}, 2013.

\bibitem{wordnet}
C.~Fellbaum, \emph{{WordNet}: An electronic lexical database}.\hskip 1em plus
0.5em minus 0.4em\relax Blackwell Books, 1998.

\bibitem{Birds200}
P.~Welinder, S.~Branson, T.~Mita, C.~Wah, F.~Schroff, S.~Belongie, and
P.~Perona, ``{Caltech-UCSD Birds 200},'' Caltech, Tech. Rep. CNS-TR-201,
2010.

\bibitem{hjelmaas2001face}
E.~Hjelm{\aa}s and B.~Low, ``Face detection: A survey,'' \emph{CVIU}, vol.~83,
no.~3, pp. 236--274, 2001.

\bibitem{LFWTech}
G.~B. Huang, M.~Ramesh, T.~Berg, and E.~Learned-Miller, ``Labeled faces in the
wild,'' University of Massachusetts, Amherst, Tech. Rep. 07-49, October 2007.

\bibitem{ILSVRCanalysis_ICCV2013}
O.~Russakovsky, J.~Deng, Z.~Huang, A.~Berg, and L.~Fei-Fei, ``Detecting
avocados to zucchinis: what have we done, and where are we going?'' in
\emph{ICCV}, 2013.

\bibitem{shotton2009textonboost}
J.~Shotton, J.~Winn, C.~Rother, and A.~Criminisi, ``{TextonBoost} for image
understanding: Multi-class object recognition and segmentation by jointly
modeling texture, layout, and context,'' \emph{IJCV}, vol.~81, no.~1, pp.
2--23, 2009.

\bibitem{seitz2006comparison}
S.~M. Seitz, B.~Curless, J.~Diebel, D.~Scharstein, and R.~Szeliski, ``A
comparison and evaluation of multi-view stereo reconstruction algorithms,''
in \emph{CVPR}, 2006.

\bibitem{amfm_pami2011}
P.~Arbelaez, M.~Maire, C.~Fowlkes, and J.~Malik, ``Contour detection and
hierarchical image segmentation,'' \emph{PAMI}, vol.~33, no.~5, pp. 898--916,
2011.

\bibitem{lampert2009learning}
C.~Lampert, H.~Nickisch, and S.~Harmeling, ``Learning to detect unseen object
classes by between-class attribute transfer,'' in \emph{CVPR}, 2009.

\bibitem{heitz2008learning}
G.~Heitz and D.~Koller, ``Learning spatial context: Using stuff to find
things,'' in \emph{ECCV}, 2008.

\bibitem{wordbank}
R.~Sitton, \emph{Spelling Sourcebook}.\hskip 1em plus 0.5em minus 0.4em\relax
Egger Publishing, 1996.

\bibitem{berg2009finding}
T.~Berg and A.~Berg, ``Finding iconic images,'' in \emph{CVPR}, 2009.

\bibitem{torralba2011unbiased}
A.~Torralba and A.~Efros, ``Unbiased look at dataset bias,'' in \emph{CVPR},
2011.

\bibitem{douze2009evaluation}
M.~Douze, H.~J{'e}gou, H.~Sandhawalia, L.~Amsaleg, and C.~Schmid, ``Evaluation
of gist descriptors for web-scale image search,'' in \emph{CIVR}, 2009.

\bibitem{felzenszwalb2010object}
P.~Felzenszwalb, R.~Girshick, D.~McAllester, and D.~Ramanan, ``Object detection
with discriminatively trained part-based models,'' \emph{PAMI}, vol.~32,
no.~9, pp. 1627--1645, 2010.

\bibitem{voc-release5}
R.~Girshick, P.~Felzenszwalb, and D.~McAllester, ``Discriminatively trained
deformable part models, release 5,'' \emph{PAMI}, 2012.

\bibitem{zhu2012we}
X.~Zhu, C.~Vondrick, D.~Ramanan, and C.~Fowlkes, ``Do we need more training
data or better models for object detection?'' in \emph{BMVC}, 2012.

\bibitem{brox2011object}
T.~Brox, L.~Bourdev, S.~Maji, and J.~Malik, ``Object segmentation by alignment
of poselet activations to image contours,'' in \emph{CVPR}, 2011.

\bibitem{yang2012layered}
Y.~Yang, S.~Hallman, D.~Ramanan, and C.~Fowlkes, ``Layered object models for
image segmentation,'' \emph{PAMI}, vol.~34, no.~9, pp. 1731--1743, 2012.

\bibitem{ramanan2007using}
D.~Ramanan, ``Using segmentation to verify object hypotheses,'' in \emph{CVPR},
2007.

\bibitem{dai2012learning}
Q.~Dai and D.~Hoiem, ``Learning to localize detected objects,'' in \emph{CVPR},
2012.

\bibitem{rashtchian2010collecting}
C.~Rashtchian, P.~Young, M.~Hodosh, and J.~Hockenmaier, ``Collecting image
annotations using {Amazon's Mechanical Turk},'' in \emph{NAACL Workshop},
2010.

\end{thebibliography}

output bib:

% \providecommand{\url}[1]{#1}
% \csname url@samestyle\endcsname
% \providecommand{\newblock}{\relax}
% \providecommand{\bibinfo}[2]{#2}
% \providecommand{\BIBentrySTDinterwordspacing}{\spaceskip=0pt\relax}
% \providecommand{\BIBentryALTinterwordstretchfactor}{4}
% \providecommand{\BIBentryALTinterwordspacing}{\spaceskip=\fontdimen2\font plus
% \BIBentryALTinterwordstretchfactor\fontdimen3\font minus
% \fontdimen4\font\relax}
% \providecommand{\BIBforeignlanguage}[2]{{%
% \expandafter\ifx\csname l@#1\endcsname\relax
% \typeout{** WARNING: IEEEtran.bst: No hyphenation pattern has been}%
% \typeout{** loaded for the language `#1'. Using the pattern for}%
% \typeout{** the default language instead.}%
% \else
% \language=\csname l@#1\endcsname
% \fi
% #2}}
% \providecommand{\BIBdecl}{\relax}
% \BIBdecl

% \bibitem{Imagenet}
% J.~Deng, W.~Dong, R.~Socher, L.-J. Li, K.~Li, and L.~Fei-Fei, ``{ImageNet: A
% Large-Scale Hierarchical Image Database},'' in \emph{CVPR}, 2009.

% \bibitem{PASCAL}
% M.~Everingham, L.VanGool, C.~K.~I. Williams, J.~Winn, and A.~Zisserman, ``The
% {PASCAL} visual object classes ({VOC}) challenge,'' \emph{IJCV}, vol.~88,
% no.~2, pp. 303--338, Jun. 2010.

% \bibitem{SUN}
% J.~Xiao, J.~Hays, K.~A. Ehinger, A.~Oliva, and A.~Torralba, ``{SUN} database:
% Large-scale scene recognition from abbey to zoo,'' in \emph{CVPR}, 2010.

% \bibitem{Dollar2012PAMI}
% P.~Doll'ar, C.~Wojek, B.~Schiele, and P.~Perona, ``Pedestrian detection: An
% evaluation of the state of the art,'' \emph{PAMI}, vol.~34, 2012.

% \bibitem{Hinton}
% A.~Krizhevsky, I.~Sutskever, and G.~Hinton, ``{ImageNet} classification with
% deep convolutional neural networks,'' in \emph{NIPS}, 2012.

% \bibitem{GirshickDDM13}
% R.~Girshick, J.~Donahue, T.~Darrell, and J.~Malik, ``Rich feature hierarchies
% for accurate object detection and semantic segmentation,'' in \emph{CVPR},
% 2014.

% \bibitem{OverFeat}
% P.~Sermanet, D.~Eigen, S.~Zhang, M.~Mathieu, R.~Fergus, and Y.~LeCun,
% ``{OverFeat}: Integrated recognition, localization and detection using
% convolutional networks,'' in \emph{ICLR}, April 2014.

% \bibitem{farhadi2009describing}
% A.~Farhadi, I.~Endres, D.~Hoiem, and D.~Forsyth, ``Describing objects by their
% attributes,'' in \emph{CVPR}, 2009.

% \bibitem{Patterson2012SunAttributes}
% G.~Patterson and J.~Hays, ``{SUN} attribute database: Discovering, annotating,
% and recognizing scene attributes,'' in \emph{CVPR}, 2012.

% \bibitem{bourdev2009poselets}
% L.~Bourdev and J.~Malik, ``Poselets: Body part detectors trained using {3D}
% human pose annotations,'' in \emph{ICCV}, 2009.

% \bibitem{NYUDepth}
% N.~Silberman, D.~Hoiem, P.~Kohli, and R.~Fergus, ``Indoor segmentation and
% support inference from {RGBD} images,'' in \emph{ECCV}, 2012.

% \bibitem{Palmer1981}
% S.~Palmer, E.~Rosch, and P.~Chase, ``Canonical perspective and the perception
% of objects,'' \emph{Attention and performance IX}, vol.~1, p.~4, 1981.

% \bibitem{diagnosing}
% .~Hoiem, D, Y.~Chodpathumwan, and Q.~Dai, ``Diagnosing error in object
% detectors,'' in \emph{ECCV}, 2012.

% \bibitem{brostow2009semantic}
% G.~Brostow, J.~Fauqueur, and R.~Cipolla, ``Semantic object classes in video: A
% high-definition ground truth database,'' \emph{PRL}, vol.~30, no.~2, pp.
% 88--97, 2009.

% \bibitem{LabelMe}
% B.~Russell, A.~Torralba, K.~Murphy, and W.~Freeman, ``{LabelMe}: a database and
% web-based tool for image annotation,'' \emph{IJCV}, vol.~77, no. 1-3, pp.
% 157--173, 2008.

% \bibitem{bell13opensurfaces}
% S.~Bell, P.~Upchurch, N.~Snavely, and K.~Bala, ``{OpenSurfaces}: A richly
% annotated catalog of surface appearance,'' \emph{SIGGRAPH}, vol.~32, no.~4,
% 2013.

% \bibitem{ordonez2011im2text}
% V.~Ordonez, G.~Kulkarni, and T.~Berg, ``Im2text: Describing images using 1
% million captioned photographs.'' in \emph{NIPS}, 2011.

% \bibitem{Olga}
% J.~Deng, O.~Russakovsky, J.~Krause, M.~Bernstein, A.~Berg, and L.~Fei-Fei,
% ``Scalable multi-label annotation,'' in \emph{CHI}, 2014.

% \bibitem{eccv}
% T.~Lin, M.~Maire, S.~Belongie, J.~Hays, P.~Perona, D.~Ramanan, P.~Doll{'a}r,
% and C.~L. Zitnick, ``Microsoft {COCO}: Common objects in context,'' in
% \emph{ECCV}, 2014.

% \bibitem{scharstein2002taxonomy}
% D.~Scharstein and R.~Szeliski, ``A taxonomy and evaluation of dense two-frame
% stereo correspondence algorithms,'' \emph{IJCV}, vol.~47, no. 1-3, pp. 7--42,
% 2002.

% \bibitem{baker2011database}
% S.~Baker, D.~Scharstein, J.~Lewis, S.~Roth, M.~Black, and R.~Szeliski, ``A
% database and evaluation methodology for optical flow,'' \emph{IJCV}, vol.~92,
% no.~1, pp. 1--31, 2011.

% \bibitem{Caltech101}
% L.~Fei-Fei, R.~Fergus, and P.~Perona, ``Learning generative visual models from
% few training examples: An incremental bayesian approach tested on 101 object
% categories,'' in \emph{CVPR Workshop of Generative Model Based Vision
% (WGMBV)}, 2004.

% \bibitem{Caltech256}
% G.~Griffin, A.~Holub, and P.~Perona, ``Caltech-256 object category dataset,''
% California Institute of Technology, Tech. Rep. 7694, 2007.

% \bibitem{Dalal}
% N.~Dalal and B.~Triggs, ``Histograms of oriented gradients for human
% detection,'' in \emph{CVPR}, 2005.

% \bibitem{mnist}
% \BIBentryALTinterwordspacing
% Y.~Lecun and C.~Cortes, ``{The MNIST database of handwritten digits},'' 1998.
% [Online]. Available: \url{http://yann.lecun.com/exdb/mnist/}
% \BIBentrySTDinterwordspacing

% \bibitem{nene1996columbia}
% S.~A. Nene, S.~K. Nayar, and H.~Murase, ``Columbia object image library
% (coil-20),'' Columbia Universty, Tech. Rep., 1996.

% \bibitem{krizhevsky2009learning}
% A.~Krizhevsky and G.~Hinton, ``Learning multiple layers of features from tiny
% images,'' \emph{Computer Science Department, University of Toronto, Tech.
% Rep}, 2009.

% \bibitem{torralba200880}
% A.~Torralba, R.~Fergus, and W.~T. Freeman, ``80 million tiny images: A large
% data set for nonparametric object and scene recognition,'' \emph{PAMI},
% vol.~30, no.~11, pp. 1958--1970, 2008.

% \bibitem{ordonezlarge}
% V.~Ordonez, J.~Deng, Y.~Choi, A.~Berg, and T.~Berg, ``From large scale image
% categorization to entry-level categories,'' in \emph{ICCV}, 2013.

% \bibitem{wordnet}
% C.~Fellbaum, \emph{{WordNet}: An electronic lexical database}.\hskip 1em plus
% 0.5em minus 0.4em\relax Blackwell Books, 1998.

% \bibitem{Birds200}
% P.~Welinder, S.~Branson, T.~Mita, C.~Wah, F.~Schroff, S.~Belongie, and
% P.~Perona, ``{Caltech-UCSD Birds 200},'' Caltech, Tech. Rep. CNS-TR-201,
% 2010.

% \bibitem{hjelmaas2001face}
% E.~Hjelm{\aa}s and B.~Low, ``Face detection: A survey,'' \emph{CVIU}, vol.~83,
% no.~3, pp. 236--274, 2001.

% \bibitem{LFWTech}
% G.~B. Huang, M.~Ramesh, T.~Berg, and E.~Learned-Miller, ``Labeled faces in the
% wild,'' University of Massachusetts, Amherst, Tech. Rep. 07-49, October 2007.

% \bibitem{ILSVRCanalysis_ICCV2013}
% O.~Russakovsky, J.~Deng, Z.~Huang, A.~Berg, and L.~Fei-Fei, ``Detecting
% avocados to zucchinis: what have we done, and where are we going?'' in
% \emph{ICCV}, 2013.

% \bibitem{shotton2009textonboost}
% J.~Shotton, J.~Winn, C.~Rother, and A.~Criminisi, ``{TextonBoost} for image
% understanding: Multi-class object recognition and segmentation by jointly
% modeling texture, layout, and context,'' \emph{IJCV}, vol.~81, no.~1, pp.
% 2--23, 2009.

% \bibitem{seitz2006comparison}
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[tex-apprentice]

SisrFeng,

The program bbl2bib.pl converts a BBL into a BIB, by finding matches on the Math Reviews database. Your BBL is not in Mathematics, so no matches will be found an the return will be empty. I would agree that this is not very clear from the man page ...

[sisrfeng]

Is there a simple but not so smart way to search deep learning papers?

[tex-apprentice]

I would assume the only possible ways would be generic CrossRef and ArXiv, unless you know of other databases that index their work.