Reranking

We describe a method for discriminative training of a language model that makes use of syntactic features. We follow a reranking approach, where a baseline recogniser is used to produce …...

In this paper, we present a method that improves Japanese dependency parsing by using large-scale statistical information. It takes into account two kinds of informa- tion not considered in previous …...

. How to improve the rankings of the relevant documents plays a key role in information retrieval. In this paper, a re-ranking approach based on topic words pair is proposed …...

Recent work on Semantic Role Labeling (SRL) has shown that to achieve high accuracy a joint inference on the whole predicate argument structure should be ap- plied. In this paper, …...

We investigate different representational granularities for sub-lexical representation in statistical machine translation work from English to Turkish. We find that (i) rep- resenting both Turkish and English at the morpheme-level …...

This paper presents pipeline iteration, an ap- proach that uses output from later stages of a pipeline to constrain earlier stages of the same pipeline. We demonstrate sig- nificant improvements …...

The present paper is concerned with sta- tistical parsing of constituent structures in German. The paper presents four ex- periments that aim at improving parsing performance of coordinate structure: 1) …...

We propose the subtree ranking approach to parse forest reranking which is a general- ization of current perceptron-based reranking methods. For the training of the reranker, we extract competing local …...

This paper presents a novel method of improving Combinatory Categorial Grammar (CCG) parsing using features generated from Dependency Grammar (DG) parses and combined using reranking. Different grammar formalisms have different …...

AbstractIt is well known that accuracies of statistical parsers trained over Penn Treebank on test sets drawn from the same corpus tend to be overestimates of their actual parsing performance. …...

Recently there has been substantial interest in using spectral methods to learn generative se- quence models like HMMs. Spectral meth- ods are attractive as they provide globally con- sistent estimates …...

AbstractMachine translation (MT) draws from several different disciplines, making it a complex subject to teach. There are excellent pedagogical texts, but problems in MT and current algorithms for solving them …...

In this paper, we present a discrimina- tive approach for reranking discourse trees generated by an existing probabilistic dis- course parser. The reranker relies on tree kernels (TKs) to capture …...

We present an empirical study on the use of semantic information for Concept Seg- mentation and Labeling (CSL), which is an important step for semantic parsing. We represent the alternative …...

Machine transliteration is often referred to as phonetic translation. We show that transliterations incorporate information from both spelling and pronunciation, and pro- pose an effective model for joint transliter- ation …...

We present our ongoing work on large-scale Japanese-Chinese bilingual dictionary con- struction via pivot-based statistical machine translation. We utilize statistical significance pruning to control noisy translation pairs that are induced …...

In this work, we focus on the problem of news citation recommendation. The task aims to recommend news citations for both authors and readers to create and search news references. …...

AbstractGenerative neural models have recently achieved state-of-the-art results for constituency parsing. However, without a feasible search procedure, their use has so far been limited to reranking the output of external …...

AbstractA large percentage of computational tools are concentrated in a very small subset of the planet’s languages. Compounding the issue, many languages lack the high-quality linguistic annotation necessary for the …...

AbstractSequence-to-sequence models for open-domain dialogue generation tend to favor generic, uninformative responses. Past work has focused on word frequency-based approaches to improving specificity, such as penalizing responses with only common …...

AbstractSemantic parsing considers the task of transducing natural language (NL) utterances into machine executable meaning representations (MRs). While neural network-based semantic parsers have achieved impressive improvements over previous methods, results …...

AbstractThis paper describes the submission to the WMT20 shared news translation task by Samsung R&D Institute Poland. We submitted systems for six language directions: English to Czech, Czech to English, …...

AbstractReranking models enable the integration of rich features to select a better output hypothesis within an n-best list or lattice. These models have a long history in NLP, and we …...

AbstractOften questions provided to open-domain question answering systems are ambiguous. Traditional QA systems that provide a single answer are incapable of answering ambiguous questions since the question may be interpreted …...

AbstractIn this paper, we describe our NAIST-NICT-TIT submission to the WMT22 general machine translation task. We participated in this task for the English ↔ Japanese language pair. Our system is …...

AbstractThere has been a surge of interest in utilizing Knowledge Graphs (KGs) for various natural language processing/understanding tasks. The conventional mechanism to retrieve facts in KGs usually involves three steps: …...

AbstractStandard decoding approaches for conditional text generation tasks typically search for an output hypothesis with high model probability, but this may not yield the best hypothesis according to human judgments …...

AbstractHedging is a strategy for softening the impact of a statement in conversation. In reducing the strength of an expression, it may help to avoid embarrassment (more technically, “face threat”) …...

AbstractText embeddings are commonly evaluated on a small set of datasets from a single task not covering their possible applications to other tasks. It is unclear whether state-of-the-art embeddings on …...