15 research outputs found
Knowledge Base Completion: Baselines Strike Back
Many papers have been published on the knowledge base completion task in the
past few years. Most of these introduce novel architectures for relation
learning that are evaluated on standard datasets such as FB15k and WN18. This
paper shows that the accuracy of almost all models published on the FB15k can
be outperformed by an appropriately tuned baseline - our reimplementation of
the DistMult model. Our findings cast doubt on the claim that the performance
improvements of recent models are due to architectural changes as opposed to
hyper-parameter tuning or different training objectives. This should prompt
future research to re-consider how the performance of models is evaluated and
reported
Negative Human Rights as a Basis for Long-term AI Safety and Regulation
If autonomous AI systems are to be reliably safe in novel situations, they
will need to incorporate general principles guiding them to recognize and avoid
harmful behaviours. Such principles may need to be supported by a binding
system of regulation, which would need the underlying principles to be widely
accepted. They should also be specific enough for technical implementation.
Drawing inspiration from law, this article explains how negative human rights
could fulfil the role of such principles and serve as a foundation both for an
international regulatory system and for building technical safety constraints
for future AI systems
Text Understanding with the Attention Sum Reader Network
Several large cloze-style context-question-answer datasets have been
introduced recently: the CNN and Daily Mail news data and the Children's Book
Test. Thanks to the size of these datasets, the associated text comprehension
task is well suited for deep-learning techniques that currently seem to
outperform all alternative approaches. We present a new, simple model that uses
attention to directly pick the answer from the context as opposed to computing
the answer using a blended representation of words in the document as is usual
in similar models. This makes the model particularly suitable for
question-answering problems where the answer is a single word from the
document. Ensemble of our models sets new state of the art on all evaluated
datasets.Comment: Presented at ACL 201