Newest Papers
Contextual Rephrase Detection for Reducing Friction in Dialogue Systems
Zhouyi Wang, Saurabh Gupta, Jie Hao, Xing Fan, Dingcheng Li, Alexander Hanbo Li, Chenlei Guo
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
For voice assistants like Alexa, Google Assis-
tant and Siri, correctly interpreting users’ in-
tentions is of utmost importance. However,
users sometimes experience friction with these
assistants, caused by errors from different sys-
tem components or user errors such as slips
of the tongue. Users tend to rephrase their
query until they get a satisfactory response.
Rephrase detection is used to identify the
rephrases and has long been treated as a task
with pairwise input, which does not fully uti-
lize the contextual information (e.g. users’ im-
plicit feedback). To this end, we propose a con-
textual rephrase detection model ContReph
to automatically identify rephrases from multi-
turn dialogues. We showcase how to leverage
the dialogue context and user-agent interaction
signals, including user’s implicit feedback and
the time gap between different turns, which
can help significantly outperform the pairwise
rephrase detection models.
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View paper →The Final Offshoring
Jacob Rintamaki
finaloffshoring.com
No abstract available
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View paper →A Spark Neglected Burns the House
Leo Tolstoy
American Literature
No abstract available
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View paper →The Byzantine Generals Problem
LESLIE LAMPORT, ROBERT SHOSTAK, and MARSHALL PEASE
Reliable computer systems must handle malfunctioning components that give conflicting information
to different parts of the system. This situation can be expressed abstractly in terms of a group of
generals of the Byzantine army camped with their troops around an enemy city. Communicating only
by messenger, the generals must agree upon a common battle plan. However, one or more of them
may be traitors who will try to confuse the others. The problem is to find an algorithm to ensure that
the loyal generals will reach agreement. It is shown that, using only oral messages, this problem is
solvable if and only if more than two-thirds of the generals are loyal; so a single traitor can confound
two loyal generals. With unforgeable written messages, the problem is solvable for any number of generals and possible traitors. Applications of the solutions to reliable computer systems are then
discussed.
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