Bilevel Scheduled Sampling for Dialogue Generation

Exposure bias poses a common challenge in numerous natural language processing tasks, particularly in the dialog generation. In response to this issue, researchers have devised various techniques, among which scheduled sampling has proven to be an effective method for mitigating exposure bias. However, the existing state-of-the-art scheduled sampling methods solely consider the current sampling words' quality for threshold truncation sampling, which overlooks the importance of sentence-level information and the method of threshold truncation warrants further discussion. In this paper, we propose a bilevel scheduled sampling model that takes the sentence-level information into account and incorporates it with word-level quality. To enhance sampling diversity and improve the model's adaptability, we propose a smooth function that maps the combined result of sentence-level and word-level information to an appropriate range, and employ probabilistic sampling based on the mapped values instead of threshold truncation. Experiments conducted on the DailyDialog and PersonaChat datasets demonstrate the effectiveness of our proposed methods, which significantly alleviate the exposure bias problem and outperform state-of-the-art scheduled sampling methods.Comment: 13 pages, 4 figures, Natural Language Processing and Chinese Computing(NLPCC 2023) accepte

The Contribution and Prospect of 5G Technology to China's Economic Development

Since the birth of 5G, it has attracted much attention from all countries in the world. The development of 5G industry is particularly important for domestic economic development. 4G changes life, 5G changes society. 5G will not only accelerate the speed of people surfing the Internet, but also bring revolutionary changes to all aspects of social life, making people's lives, work and entertainment more convenient and diverse. The economic impact of the development of the 5G industry on China cannot be underestimated. Nowadays, information and communication technology has increasingly become a new driving force for economic development. 5G technology has already become a key technology pursuit for countries to compete for the status of world power, and it has also become an indispensable part of contemporary economic and social development. We should give full play to the government's guiding role, and work with network giants to build a new platform for cooperation, promote coordinated industrial development, achieve win-win results, and promote economic and social prosperity and development

A Literature Review of the "Burning Money" Behavior of Internet Products

This article mainly studies the current status of the operation of the “burning money model” of Internet products, expounds and analyzes the disadvantages of this operating model, studies the practical effects brought by the “burning money model”, and explores the development direction of future Internet products. Domestic scholars have done a lot of research on the development of Internet products in the future and have achieved certain results. This article aims to discuss the development model of China’s Internet products, summarize the current “burning money” behavior in the operation process of Internet products, and combine the development situation of China’s Internet in the new era to make suggestions for the future development of Internet products

Big Data Platform Architecture Under The Background of Financial Technology

With the rise of the concept of financial technology, financial and technology gradually in-depth integration, scientific and technological means to become financial product innovation, improve financial efficiency and reduce financial transaction costs an important driving force. In this context, the new technology platform is from the business philosophy, business model, technical means, sales, internal management, and other dimensions to re-shape the financial industry. In this paper, the existing big data platform architecture technology innovation, adding space-time data elements, combined with the insurance industry for practical analysis, put forward a meaningful product circle and customer circle.Comment: 4 pages, 3 figures, 2018 International Conference on Big Data Engineering and Technolog

The Voluntary Adoption of an Audit Committee and Earnings Quality: Evidence from China

This study investigates the causes and consequences of firms’ voluntarily adoption of the audit committees, using a sample of China’s listed firms from 2001 to 2008 when no regulations or listing rules existed for audit committees. We develop and test two hypotheses. The ‘‘demand’’ hypothesis holds that firms with greater agency costs are more likely to have an audit committee. In contract , the ‘‘opportunistic behavior’’ hypothesis predicts that the bargaining power of the CEO relative to the rest of the board of directors will determine the level of composition of the board and the extent of board monitoring. In this study, we empirically investigate the validity of these two hypotheses and further compare the quality of accounting numbers produced by China’s listed firms with and without an audit committee, in order to shed light on the determinants and effectiveness of audit committee in emerging markets

Conflict and Political Struggle in the education of Japan (1)

The purpose of this paper is to analyze the political struggle between the LDP government and the Japanese Teachers' Union in Japanese education during the 1980s and 1990s. A characteristic of Japanese education was the severe conflict between the government and the teachers' union. Not only ideological issues such as the national flag and national anthem, but also all systems such as teacher salary, teacher position system, teacher evaluation system, the government and teachers union violently conflicted. Many observers attribute the conflict between the government and the faculty union to an uncompromising political struggle between the “right” government and the “left” union. However, the faculty union was a complex organization and was not inseparably linked to any particular political party. In addition, union behavior was often political, but not only that, but factors such as maintaining the organization and improving the treatment of union members were also important to the union. This paper analyzes the battle between the government and the union that occurred in Hiroshima Prefecture at the time when the "big compromise" between the government and the union was established. Through this analysis, we try to document a part of the history of education in the 1990s and to clarify the nature of political struggles over Japanese education

Program analysis for quantitative-reachability properties

Program analysis studies the execution behaviors of computer programs including programs’ safety behavior, privacy behavior, resource usage, etc. The kind of program analysis on the safety behavior of a program involves analyzing if a particular line of code leaks a secret and how much secret is leaked by this line of code. When studying the resource usage of a program, certain program analysis mainly focuses on analyzing whether a piece of code consumes a certain resource and how much resource is used by this piece of code. Yet another kind of program analysis is studying the program privacy behavior by analyzing whether a specific private data is dependent on other data and how many times they are dependent during multiple executions. We notice that when studying the aforementioned behaviors, there are two dominant program properties that we are analyzing – “How Much” and “Whether”, namely quantitative properties and reachability properties. In other words, we are analyzing the kind of program property that contains two sub-properties – quantitative and reachability. A property is a hyper-property if it has two or more sub-properties. For the class of properties that has quantitative and reachability sub-properties, I refer to them as quantitative-reachability hyperproperties. Most existing program analysis methods can analyze only one subproperty of a program’s quantitative-reachability hyper-property. For example, the reachability analysis methods only tell us whether some code pieces are executed, whether the confidential data is leaked, whether certain data relies on another data, etc., which are only the reachability sub-properties. These analysis methods do not address how many times or how long these properties hold with respect to some particular code or data. Quantitative analysis methods, such as program complexity analysis, resource cost analysis, execution time estimation, etc., only tell us the upper bound on the overall quantity, i.e., the quantitative sub-property. However, these quantities are not associated with a specific piece of code, program location, private data, etc., which are related to the reachability sub-properties. This thesis presents new program analysis methodology for analyzing two representative quantitative-reachability properties. The new methodology mitigates the limitations in both reachability analysis methods and quantitative analysis methods and help to control the program’s execution behaviors in higher granularity. The effectiveness of the new analysis method is validated through prototype implementations and experimental evaluations. The first noteworthy quantitative-reachability property I look into is the adaptivity in the programs that implement certain adaptive data analyses. Data analyses are usually designed to identify some properties of the population from which the data are drawn, generalizing beyond the specific data sample. For this reason, data analyses are often designed in a way that guarantees that they produce a low generalization error. An adaptive data analysis can be seen as a process composed by multiple queries interrogating some data, where the choice of which query to run next may rely on the results of previous queries. The generalization error of each individual query/analysis can be controlled by using an array of well-established statistical techniques. However, when queries are arbitrarily composed, the different errors can propagate through the chain of different queries and result in high generalization error. To address this issue, data analysts are designing several techniques that not only guarantee bounds on the generalization errors of single queries, but that also guarantee bounds on the generalization error of the composed analyses. The choice of which of these techniques to use, often depends on the chain of queries that an adaptive data analysis can generate, intuitively the adaptivity level in an adaptive data analysis. To help analysts with identifying which technique to use to control their generalization error, we consider adaptive data analyses implemented as while-like programs, and we design a program analysis framework. In this framework, we first formalize the intuitive notion of adaptivity as a quantitative-reachability property, which is a key measure of an adaptive data analysis to choose the appropriate technique. Then we design a program analysis algorithm that estimates a sound upper bound on the adaptivity of the program that implements an adaptive data analysis. We also implement my program analysis and show that it can help to analyze the adaptivity of several concrete data analyses with different adaptivity structures. As a continuation of the previous work, to get a more precise bound on a program’s adaptivity level, I look at another quantitative-reachability hyper-property – the number of times a given location inside a procedure is visited during the program execution. The upper bound on this hyper-property is referred to as the reachability-bound. It can help to improve the program analysis results when studying other different program features. For example, the reachability-bound on each program location can be used by some resource cost analysis techniques to compute a precise bound on a program’s worst-case resource consumption. When we analyze the adaptivity in an adaptive data analysis program as discussed above, the accuracy of my program analysis result can also be improved through a tight reachability-bound on every program location. Some existing program complexity analysis methods can be repurposed to analyze and estimate the reachability-bound. However, these methods focus only on the overall quantity and ignore the path sensitivity in the program. For this reason, the reachability-bounds of the locations in different sub-procedures are usually over-approximated. As far as we know, there is no general analysis algorithm that computes the reachability-bound for every program location directly and path-sensitively. To this end, I present a pathsensitive reachability-bound algorithm, which exploit the path sensitivity to compute a precise reachability-bound for every program location. We implement this path-sensitive reachability-bound algorithm in a prototype, and report on an experimental comparison with state-of-art tools over four different sets of benchmarks

Integrated Life Cycle Economic and Environmental Impact Assessment for Transportation Infrastructure: A Review

In order to realize the sustainable development of transportation infrastructure, more and more attention has been paid to the multi-scheme selection method of road engineering, while the existing life cycle cost analysis (LCCA) and life cycle assessment (LCA) methods are often isolated from each other, which cannot better realize the comprehensive evaluation of road life cycle. This chapter will review and summarize the development of LCCA and LCA systematically. Pointing out the existing problems in current research, the idea of integrated evaluation method combining LCA and LCCA is proposed. It puts forward the future development direction based on the deficiency of the current research results and provides useful reference for the popularization and application of the life cycle methods in road engineering