39 research outputs found
A Lipid Rafts Theory of Alzheimer's Disease
I present a theory of Alzheimer's Disease (AD) that explains its symptoms,
pathology, and risk factors. To do this, I introduce a new theory of brain
plasticity that elucidates the physiological roles of AD-related agents. New
events generate synaptic and branching candidates competing for long-term
enhancement. Competition resolution crucially depends on the formation of
membrane lipid rafts, which requires astrocyte-produced cholesterol. Sporadic
AD is caused by impaired formation of plasma membrane lipid rafts, which
prevents the conversion of short- to long-term memory, and yields excessive tau
phosphorylation, intracellular cholesterol accumulation, synaptic dysfunction,
and neurodegeneration. Amyloid beta (Abeta) production is promoted by
cholesterol during the switch to competition resolution, and cholesterol
accumulation stimulates chronic Abeta production, secretion, and aggregation.
The theory addresses all of the major established facts known about the
disease, and is supported by strong evidence.Comment: 44 pages, 4 figures. Invite
A Transition-Based Directed Acyclic Graph Parser for UCCA
We present the first parser for UCCA, a cross-linguistically applicable
framework for semantic representation, which builds on extensive typological
work and supports rapid annotation. UCCA poses a challenge for existing parsing
techniques, as it exhibits reentrancy (resulting in DAG structures),
discontinuous structures and non-terminal nodes corresponding to complex
semantic units. To our knowledge, the conjunction of these formal properties is
not supported by any existing parser. Our transition-based parser, which uses a
novel transition set and features based on bidirectional LSTMs, has value not
just for UCCA parsing: its ability to handle more general graph structures can
inform the development of parsers for other semantic DAG structures, and in
languages that frequently use discontinuous structures.Comment: 16 pages; Accepted as long paper at ACL201
BLEU is Not Suitable for the Evaluation of Text Simplification
BLEU is widely considered to be an informative metric for text-to-text
generation, including Text Simplification (TS). TS includes both lexical and
structural aspects. In this paper we show that BLEU is not suitable for the
evaluation of sentence splitting, the major structural simplification
operation. We manually compiled a sentence splitting gold standard corpus
containing multiple structural paraphrases, and performed a correlation
analysis with human judgments. We find low or no correlation between BLEU and
the grammaticality and meaning preservation parameters where sentence splitting
is involved. Moreover, BLEU often negatively correlates with simplicity,
essentially penalizing simpler sentences.Comment: Accepted to EMNLP 2018 (Short papers
Content Differences in Syntactic and Semantic Representations
Syntactic analysis plays an important role in semantic parsing, but the
nature of this role remains a topic of ongoing debate. The debate has been
constrained by the scarcity of empirical comparative studies between syntactic
and semantic schemes, which hinders the development of parsing methods informed
by the details of target schemes and constructions. We target this gap, and
take Universal Dependencies (UD) and UCCA as a test case. After abstracting
away from differences of convention or formalism, we find that most content
divergences can be ascribed to: (1) UCCA's distinction between a Scene and a
non-Scene; (2) UCCA's distinction between primary relations, secondary ones and
participants; (3) different treatment of multi-word expressions, and (4)
different treatment of inter-clause linkage. We further discuss the long tail
of cases where the two schemes take markedly different approaches. Finally, we
show that the proposed comparison methodology can be used for fine-grained
evaluation of UCCA parsing, highlighting both challenges and potential sources
for improvement. The substantial differences between the schemes suggest that
semantic parsers are likely to benefit downstream text understanding
applications beyond their syntactic counterparts.Comment: NAACL-HLT 2019 camera read