To the instructor+TAs:
-  Fill the table below with scores. (Send this separately to Prof. Saxena + TAs with paper title in the email.)

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Scores are from 1-10 (1 being worst, 6 average, and 10 "perfect"):
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A. Clarity:
B. Quality:
C. Amount of work:
D. Originality:
E. Experiments: 
F. Other criterion: 

Overall score (out of 10):
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To the authors:
-  For each of the six categories (A-F), please explain in a few lines how well does the paper do and why.
-  Give detailed comments to the authors.


A. Clarity

Is the paper clearly written? Is it well-organized? (If not, feel free to make
suggestions to improve the manuscript.) Does it adequately inform the reader?
Is the problem statement and approach clear?


B. Quality

Is the paper technically sound?   Does the formulation of the problem makes sense.


C. Amount of Work

Do some parts of the project required a lot of work to be done?
(E.g., data collection, robotic experiments, or others)  


D. Originality

Are the problems or approaches new? Is this a novel combination of familiar
techniques?  Is the application new? 

Is it clear how this work differs from previous work? Is related work
adequately referenced/compared with recent papers?  Does the paper address a
difficult problem in a better way than previous research? 


E.  Experiments

Is the amount/type of data standard for the community?  If it is a new dataset,
does this adequately reflects the problem?  Are there some basic baselines
that the authors compared against?  How does it compare to previous works in the
area?

Does it advance the state of the art in a demonstrable way? Does it
provide unique data, unique conclusions on existing data, or a unique
theoretical or pragmatic approach?


F.  Any other criterion.

Each work is unique. Please mention any other category that is noticeable in this paper.



Notes to the author:
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Use this space to give detailed comments to the authors, etc.