1,917 research outputs found
A Casual Tour Around a Circuit Complexity Bound
I will discuss the recent proof that the complexity class NEXP
(nondeterministic exponential time) lacks nonuniform ACC circuits of polynomial
size. The proof will be described from the perspective of someone trying to
discover it.Comment: 21 pages, 2 figures. An earlier version appeared in SIGACT News,
September 201
Text to 3D Scene Generation with Rich Lexical Grounding
The ability to map descriptions of scenes to 3D geometric representations has
many applications in areas such as art, education, and robotics. However, prior
work on the text to 3D scene generation task has used manually specified object
categories and language that identifies them. We introduce a dataset of 3D
scenes annotated with natural language descriptions and learn from this data
how to ground textual descriptions to physical objects. Our method successfully
grounds a variety of lexical terms to concrete referents, and we show
quantitatively that our method improves 3D scene generation over previous work
using purely rule-based methods. We evaluate the fidelity and plausibility of
3D scenes generated with our grounding approach through human judgments. To
ease evaluation on this task, we also introduce an automated metric that
strongly correlates with human judgments.Comment: 10 pages, 7 figures, 3 tables. To appear in ACL-IJCNLP 201
Acquiring Word-Meaning Mappings for Natural Language Interfaces
This paper focuses on a system, WOLFIE (WOrd Learning From Interpreted
Examples), that acquires a semantic lexicon from a corpus of sentences paired
with semantic representations. The lexicon learned consists of phrases paired
with meaning representations. WOLFIE is part of an integrated system that
learns to transform sentences into representations such as logical database
queries. Experimental results are presented demonstrating WOLFIE's ability to
learn useful lexicons for a database interface in four different natural
languages. The usefulness of the lexicons learned by WOLFIE are compared to
those acquired by a similar system, with results favorable to WOLFIE. A second
set of experiments demonstrates WOLFIE's ability to scale to larger and more
difficult, albeit artificially generated, corpora. In natural language
acquisition, it is difficult to gather the annotated data needed for supervised
learning; however, unannotated data is fairly plentiful. Active learning
methods attempt to select for annotation and training only the most informative
examples, and therefore are potentially very useful in natural language
applications. However, most results to date for active learning have only
considered standard classification tasks. To reduce annotation effort while
maintaining accuracy, we apply active learning to semantic lexicons. We show
that active learning can significantly reduce the number of annotated examples
required to achieve a given level of performance
Lazy Stream Programming in Prolog
In recent years, stream processing has become a prominent approach for
incrementally handling large amounts of data, with special support and
libraries in many programming languages. Unfortunately, support in Prolog has
so far been lacking and most existing approaches are ad-hoc. To remedy this
situation, we present lazy stream generators as a unified Prolog interface for
stateful computations on both finite and infinite sequences of data that are
produced incrementally through I/O and/or algorithmically.
We expose stream generators to the application programmer in two ways: 1)
through an abstract sequence manipulation API, convenient for defining custom
generators, and 2) as idiomatic lazy lists, compatible with many existing list
predicates. We define an algebra of stream generator operations that extends
Prolog via an embedded language interpreter, provides a compact notation for
composing generators and supports moving between the two isomorphic
representations.
As a special instance, we introduce answer stream generators that encapsulate
the work of coroutining first-class logic engines and support interoperation
between forward recursive AND-streams and backtracking-generated OR-streams.
Keywords: lazy stream generators, lazy lists, first-class logic engines,
stream combinators, AND-stream / OR-stream interoperation, Prolog extensionsComment: In Proceedings ICLP 2019, arXiv:1909.0764
- …