Differentiable Instruction Optimization for Cross-Task Generalization

Instruction tuning has been attracting much attention to achieve generalization ability across a wide variety of tasks. Although various types of instructions have been manually created for instruction tuning, it is still unclear what kind of instruction is optimal to obtain cross-task generalization ability. This work presents instruction optimization, which optimizes training instructions with respect to generalization ability. Rather than manually tuning instructions, we introduce learnable instructions and optimize them with gradient descent by leveraging bilevel optimization. Experimental results show that the learned instruction enhances the diversity of instructions and improves the generalization ability compared to using only manually created instructions.Comment: 14pages, 6 figures, accepted for Findings of ACL202

SciReviewGen: A Large-scale Dataset for Automatic Literature Review Generation

Automatic literature review generation is one of the most challenging tasks in natural language processing. Although large language models have tackled literature review generation, the absence of large-scale datasets has been a stumbling block to the progress. We release SciReviewGen, consisting of over 10,000 literature reviews and 690,000 papers cited in the reviews. Based on the dataset, we evaluate recent transformer-based summarization models on the literature review generation task, including Fusion-in-Decoder extended for literature review generation. Human evaluation results show that some machine-generated summaries are comparable to human-written reviews, while revealing the challenges of automatic literature review generation such as hallucinations and a lack of detailed information. Our dataset and code are available at https://github.com/tetsu9923/SciReviewGen.Comment: ACL findings 2023 (to be appeared). arXiv admin note: text overlap with arXiv:1810.04020 by other author

Bariatric Surgery on Type 2 Diabetes Mellitus Patients in Japan

Article信州医学雑誌 59(4): 273-279(2011)departmental bulletin pape

Predictive Process Model Monitoring using Recurrent Neural Networks

The field of predictive process monitoring focuses on modelling future characteristics of running business process instances, typically by either predicting the outcome of particular objectives (e.g. completion (time), cost), or next-in-sequence prediction (e.g. what is the next activity to execute). This paper introduces Processes-As-Movies (PAM), a technique that provides a middle ground between these predictive monitoring. It does so by capturing declarative process constraints between activities in various windows of a process execution trace, which represent a declarative process model at subsequent stages of execution. This high-dimensional representation of a process model allows the application of predictive modelling on how such constraints appear and vanish throughout a process' execution. Various recurrent neural network topologies tailored to high-dimensional input are used to model the process model evolution with windows as time steps, including encoder-decoder long short-term memory networks, and convolutional long short-term memory networks. Results show that these topologies are very effective in terms of accuracy and precision to predict a process model's future state, which allows process owners to simultaneously verify what linear temporal logic rules hold in a predicted process window (objective-based), and verify what future execution traces are allowed by all the constraints together (trace-based)

Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance

This paper presents a novel unsupervised abstractive summarization method for opinionated texts. While the basic variational autoencoder-based models assume a unimodal Gaussian prior for the latent code of sentences, we alternate it with a recursive Gaussian mixture, where each mixture component corresponds to the latent code of a topic sentence and is mixed by a tree-structured topic distribution. By decoding each Gaussian component, we generate sentences with tree-structured topic guidance, where the root sentence conveys generic content, and the leaf sentences describe specific topics. Experimental results demonstrate that the generated topic sentences are appropriate as a summary of opinionated texts, which are more informative and cover more input contents than those generated by the recent unsupervised summarization model (Bra\v{z}inskas et al., 2020). Furthermore, we demonstrate that the variance of latent Gaussians represents the granularity of sentences, analogous to Gaussian word embedding (Vilnis and McCallum, 2015).Comment: accepted to TACL, pre-MIT Press publication versio

スマートフォン ト インターネット オ モチイタ トクシマ ケンリツ カイフ ビョウイン エンカク イリョウ シエン システム k-support ノ ドウニュウ

Because a specialist in general medical treatment lacked the Kaifu area of South Tokushima absolutely, we forced a limited doctor to many burdens and performed medical treatment while I always carried risks on my back for the disease except the specialty domain. A stroke specialist in particular is an absent medical depopulated area, and it is difficult to perform the rt-PA IV therapy that is a standard therapy for a stroke for the immediate nature period. Using remote video diagnosis treatment supporting system SYNAPSE ERm that was the smartphone application that FUJIFILM developed for the purpose of canceling these, we introduced smartphone and Tokushima Prefectural Kaifu Hospital remoteness medical treatment support system （k-support） by the Internet as area medical treatment support in February, 2013. This system can provide image information and patient information such as CT or the MRI to a tablet phone and the smartphone of Tokushima Prefectural Kaifu Hospital full-time employment doctors and the doctors who support it, and work in a House in real time. In other words, we can obtain necessary information without asking the when and where and can send appropriate instructions, advice to the Tokushima Prefectural Kaifu Hospital medical attendant from a specialist for it. After introduction, the treatment with this system in 58 emergency patients was carried out in seven months until August 31. The example letting the wide area present the smartphone such as this system and a remote medical treatment support system using the Internet in the medical depopulated area is the first trial in this country

Complications of Flex URS for Renal and Ureteral Calculi during the Learning Curve

Background: The flexible ureterorenoscope (URS) and associated devices have developed rapidly. However, despite its therapeutic benefits, URS may be associated with some complications. To the best of our knowledge, there are no studies discussing the complications of flexURS during the learning curve. Methods: A retrospective review of the records of patients who underwent flexURS from January 2005 to June 2013 was performed. To compare the complications after the introduction of flexURS, patients were divided into four groups based on the surgeon’s training experience, that is, based on the number of cases performed by the surgeon. A total of 219 cases underwent flexURS. Groups 1, 2, 3, and 4 included 35, 50, 50, and 84 cases, respectively. The complications were classified using the Clavien system (I–IV). Results: The mean operation time and stone-free rate were significantly different (p < 0.001, p = 0.013, respectively). The total complication rates were 13.6, 10, 8.3, and 3.2%, respectively (p = 0.068). The more the surgeon’s experience, the less was the complication rate. Despite our best efforts, the incidence of urosepsis was not reduced (p = 0.902). Conclusions: To reduce severe complications, it is necessary to have performed about 100 cases. Increased surgeon experience tended to decrease the risk of severe complications, but the incidence of urosepsis was not reduced