Zobrazeno 1 - 10
of 204
pro vyhledávání: '"Gildea, Daniel"'
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 7, Pp 19-31 (2019)
It is intuitive that semantic representations can be useful for machine translation, mainly because they can help in enforcing meaning preservation and handling data sparsity (many sentences correspond to one meaning) of machine translation models. O
Externí odkaz:
https://doaj.org/article/86d54844cecd4a84ace6a747a8e54b02
Autor:
Yu, Chen, Gildea, Daniel
AMR parsing is the task that maps a sentence to an AMR semantic graph automatically. We focus on the breadth-first strategy of this task, which was proposed recently and achieved better performance than other strategies. However, current models under
Externí odkaz:
http://arxiv.org/abs/2211.03922
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence, 36(10) (2022) 10849-10857
Utterance rewriting aims to recover coreferences and omitted information from the latest turn of a multi-turn dialogue. Recently, methods that tag rather than linearly generate sequences have proven stronger in both in- and out-of-domain rewriting se
Externí odkaz:
http://arxiv.org/abs/2206.11218
Autor:
Jin, Lisa, Gildea, Daniel
Graph encoders in AMR-to-text generation models often rely on neighborhood convolutions or global vertex attention. While these approaches apply to general graphs, AMRs may be amenable to encoders that target their tree-like structure. By clustering
Externí odkaz:
http://arxiv.org/abs/2108.12304
Autor:
Jin, Lisa, Gildea, Daniel
Text generation from AMR requires mapping a semantic graph to a string that it annotates. Transformer-based graph encoders, however, poorly capture vertex dependencies that may benefit sequence prediction. To impose order on an encoder, we locally co
Externí odkaz:
http://arxiv.org/abs/2108.12300
Analyzing patterns in a sequence of events has applications in text analysis, computer programming, and genomics research. In this paper, we consider the all-window-length analysis model which analyzes a sequence of events with respect to windows of
Externí odkaz:
http://arxiv.org/abs/2011.14460
Semiring parsing is an elegant framework for describing parsers by using semiring weighted logic programs. In this paper we present a generalization of this concept: latent-variable semiring parsing. With our framework, any semiring weighted logic pr
Externí odkaz:
http://arxiv.org/abs/2006.04232
Autor:
Riley, Parker, Gildea, Daniel
Recent embedding-based methods in unsupervised bilingual lexicon induction have shown good results, but generally have not leveraged orthographic (spelling) information, which can be helpful for pairs of related languages. This work augments a state-
Externí odkaz:
http://arxiv.org/abs/2002.00037
Autor:
Jin, Lisa, Gildea, Daniel
Text generation from AMR involves emitting sentences that reflect the meaning of their AMR annotations. Neural sequence-to-sequence models have successfully been used to decode strings from flattened graphs (e.g., using depth-first or random traversa
Externí odkaz:
http://arxiv.org/abs/1912.01682
Medical relation extraction discovers relations between entity mentions in text, such as research articles. For this task, dependency syntax has been recognized as a crucial source of features. Yet in the medical domain, 1-best parse trees suffer fro
Externí odkaz:
http://arxiv.org/abs/1911.04123