Enumeration of Extractive Oracle Summaries

To analyze the limitations and the future directions of the extractive summarization paradigm, this paper proposes an Integer Linear Programming (ILP) formulation to obtain extractive oracle summaries in terms of ROUGE-N. We also propose an algorithm that enumerates all of the oracle summaries for a set of reference summaries to exploit F-measures that evaluate which system summaries contain how many sentences that are extracted as an oracle summary. Our experimental results obtained from Document Understanding Conference (DUC) corpora demonstrated the following: (1) room still exists to improve the performance of extractive summarization; (2) the F-measures derived from the enumerated oracle summaries have significantly stronger correlations with human judgment than those derived from single oracle summaries.Comment: 12 page

Utilizing Features of Verbs in Statistical Zero Pronoun Resolution for Japanese Speech

PACLIC 23 / City University of Hong Kong / 3-5 December 200

BaseNP Supersense Tagging for Japanese Texts

PACLIC 23 / City University of Hong Kong / 3-5 December 200

Parathyroid Diseases and Animal Models

Circulating calcium and phosphate are tightly regulated by three hormones: the active form of vitamin D (1,25-dihydroxyvitamin D), fibroblast growth factor (FGF)-23, and parathyroid hormone (PTH). PTH acts to stimulate a rapid increment in serum calcium and has a crucial role in calcium homeostasis. Major target organs of PTH are kidney and bone. The oversecretion of the hormone results in hypercalcemia, caused by increased intestinal calcium absorption, reduced renal calcium clearance, and mobilization of calcium from bone in primary hyperparathyroidism. In chronic kidney disease, secondary hyperparathyroidism of uremia is observed in its early stages, and this finally develops into the autonomous secretion of PTH during maintenance hemodialysis. Receptors in parathyroid cells, such as the calcium-sensing receptor, vitamin D receptor, and FGF receptor (FGFR)-Klotho complex have crucial roles in the regulation of PTH secretion. Genes such as Cyclin D1, RET, MEN1, HRPT2, and CDKN1B have been identified in parathyroid diseases. Genetically engineered animals with these receptors and the associated genes have provided us with valuable information on the patho-physiology of parathyroid diseases. The application of these animal models is significant for the development of new therapies

WSPAlign: Word Alignment Pre-training via Large-Scale Weakly Supervised Span Prediction

Most existing word alignment methods rely on manual alignment datasets or parallel corpora, which limits their usefulness. Here, to mitigate the dependence on manual data, we broaden the source of supervision by relaxing the requirement for correct, fully-aligned, and parallel sentences. Specifically, we make noisy, partially aligned, and non-parallel paragraphs. We then use such a large-scale weakly-supervised dataset for word alignment pre-training via span prediction. Extensive experiments with various settings empirically demonstrate that our approach, which is named WSPAlign, is an effective and scalable way to pre-train word aligners without manual data. When fine-tuned on standard benchmarks, WSPAlign has set a new state-of-the-art by improving upon the best-supervised baseline by 3.3~6.1 points in F1 and 1.5~6.1 points in AER. Furthermore, WSPAlign also achieves competitive performance compared with the corresponding baselines in few-shot, zero-shot and cross-lingual tests, which demonstrates that WSPAlign is potentially more practical for low-resource languages than existing methods.Comment: To appear at ACL 202

Extending Word-Level Quality Estimation for Post-Editing Assistance

We define a novel concept called extended word alignment in order to improve post-editing assistance efficiency. Based on extended word alignment, we further propose a novel task called refined word-level QE that outputs refined tags and word-level correspondences. Compared to original word-level QE, the new task is able to directly point out editing operations, thus improves efficiency. To extract extended word alignment, we adopt a supervised method based on mBERT. To solve refined word-level QE, we firstly predict original QE tags by training a regression model for sequence tagging based on mBERT and XLM-R. Then, we refine original word tags with extended word alignment. In addition, we extract source-gap correspondences, meanwhile, obtaining gap tags. Experiments on two language pairs show the feasibility of our method and give us inspirations for further improvement