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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Beichen Zhang Kun Zhou Xilin Wei Wayne Xin Zhao Jing Sha Shijin Wang Ji-Rong Wen Gaoling School of Artificial Intelligence Renmin University of China and Beijing Key Laboratory of Big Data Management and Analysis Methods School of Information Renmin University of China and Beijing Key Laboratory of Big Data Management and Analysis Methods College of Computer Science Sichuan University iFLYTEK Research iFLYTEK Research and iFLYTEK AI Research (Central China) Gaoling School of Artificial Intelligence Renmin University of China and School of Information Renmin University of China and Beijing Key Laboratory of Big Data Management and Analysis Methods

Chain-of-thought prompting (CoT) and tool augmentation have been validated in recent work as effective practices for improving large language models (LLMs) to perform step-by-step reasoning on complex math-related tasks. However, most existing math reasoning datasets may not be able to fully evaluate and analyze the ability of LLMs in manipulating tools and performing reasoning, as they often only require very few invocations of tools or miss annotations for evaluating intermediate reasoning steps, thus supporting only outcome evaluation. To address the issue, we construct CARP, a new Chinese dataset consisting of 4,886 computation-intensive algebra problems with formulated annotations on intermediate steps, facilitating the evaluation of the intermediate reasoning process. In CARP, we test four LLMs with CoT prompting, and find that they are all prone to make mistakes at the early steps of the solution, leading to incorrect answers. Based on this finding, we propose a new approach that can facilitate the deliberation on reasoning steps with tool interfaces, namely DELI. In DELI, we first initialize a step-by-step solution based on retrieved exemplars, then iterate two deliberation procedures that check and refine the intermediate steps of the generated solution, from both tool manipulation and natural language reasoning perspectives, until solutions converge or the maximum iteration is achieved. Experimental results on CARP and six other datasets show that the proposed DELI mostly outperforms competitive baselines, and can further boost the performance of existing CoT methods. Our data and code are available at https://***/RUCAIBox/CARP.

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Research on the Integration of Curriculum Ideological and Political Elements into Communication Principles

Research on the Integration of Curriculum Ideological and Po...

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International Conference on Educational and Information Technology (ICEIT)

作者： Rong Geng Chunhong Cao Ce Ji School of Computer Science and Technology Northeast University Shenyang China Teaching Innovation and Research Center of Northeastern University Shenyang China

ISBN: (数字)9781665422956

ISBN: (纸本)9781665446471

The proposal of curriculum ideological and political education puts forward new requirements for the reform of specialized curriculum teaching in the new era. As the core professional course of communication and electronics, the course of communication principles plays an important role in the cultivation of students' professional basic theoretical knowledge and practical ability. This paper analyzes the importance of integrating ideological and political education into the course of communication principles, deeply excavates the ideological and political elements contained in the course of communication principles, and puts forward requirements for the teachers and evaluation system of teaching, thus providing a reference for the comprehensive training of communication and electronic talents.

关键词： Training Education Proposals Information technology

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Equivariant Graph Hierarchy-Based Neural Networks

arXiv

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arXiv 2022年

作者： Han, Jiaqi Huang, Wenbing Xu, Tingyang Rong, Yu Department of Computer Science and Technology Tsinghua University China Gaoling School of Artificial Intelligence Renmin University of China China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China Tencent AI Lab China

Equivariant Graph neural Networks (EGNs) are powerful in characterizing the dynamics of multi-body physical systems. Existing EGNs conduct flat message passing, which, yet, is unable to capture the spatial/dynamical hierarchy for complex systems particularly, limiting substructure discovery and global information fusion. In this paper, we propose Equivariant Hierarchy-based Graph Networks (EGHNs) which consist of the three key components: generalized Equivariant Matrix Message Passing (EMMP), E-Pool and E-UnPool. In particular, EMMP is able to improve the expressivity of conventional equivariant message passing, E-Pool assigns the quantities of the low-level nodes into high-level clusters, while E-UnPool leverages the high-level information to update the dynamics of the low-level nodes. As their names imply, both E-Pool and E-UnPool are guaranteed to be E(n)-equivariant to meet the physical symmetry. Considerable experimental evaluations verify the effectiveness of our EGHN on several applications including multi-object dynamics simulation, motion capture, and protein dynamics modeling. © 2022, CC BY.

关键词： Message passing

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Democratizing engineering education: An online Bachelor of science in Engineering degree

Democratizing engineering education: An online Bachelor of S...

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Frontiers in Education (FIE) Conference

作者： Nick A. Stites Janet L. Yowell Rhonda Hoenigman William Kuskin Abigail B. Rose University of Colorado Boulder Integrated Teaching & Learning Program Boulder CO USA Computer Science Department University of Colorado Boulder Boulder CO USA English Department University of Colorado Boulder Boulder CO USA University of Colorado Boulder Engineering Digital Education Boulder CO USA

The College of Engineering & Applied science at the University of Colorado Boulder proposes a low-cost, online, accredited Bachelor of science in Engineering (BSE) degree. The BSE will provide a pathway for community college (CC) students, or students with similar transfer credits, to complete a degree in engineering at a cost similar to attending CC. The educationally underserved communities across Colorado are often low-income, racially and ethnically diverse, and rural; the BSE's primary goal is to provide access to an engineering education for these students and, thus, open pathways to high-demand, high-wage careers. The BSE will reach an underserved population of learners who can stay in their local community while simultaneously pursuing an engineering education. A fully online, ABET-accredited engineering degree is surprisingly novel-only nine other online engineering degrees in the nation are accredited-but an R1-level university degree at a near-community-college cost is unprecedented. The BSE will invite the institution's best instructors to innovate in online education-virtual labs, team-based projects, flipped asynchronous discussions, and hybrid-learning activities. Student success support will include wrap-around advising to foster the development of the academic, affective, financial, and career support that students need to succeed in engineering. The BSE will utilize five administrative affordances: 1) success coaches to provide wrap-around support and guidance to students; 2) course facilitators who provide personalized support; 3) stackable credentials; 4) eight-week semesters, allowing students to quickly complete portions of their education; and 5) mentorship programming to foster community and to help students develop their (inter)disciplinary identity. The online BSE creates a new pathway for underserved students to matriculate to a flagship public research university for a degree in engineering. This work-in-progress outlines the proposed str

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Straightening skewed markets with an index tracking optimizationless portfolio

arXiv

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arXiv 2022年

作者： Bufalo, Daniele Bufalo, Michele Cesarone, Francesco Orlando, Giuseppe University of Bari Department of Computer Science Italy Sapienza University of Rome Department of Methods and Models for Economics Territory and Finance Italy Roma Tre University Department of Business Studies Italy University of Bari Department of Finance and Economics Italy

Among professionals and academics alike, it is well known that active portfolio management is unable to provide additional risk-adjusted returns relative to their benchmarks. For this reason, passive wealth management has emerged in recent decades to offer returns close to benchmarks at a lower cost. In this article, we first refine the existing results on the theoretical properties of oblique Brownian motion. Then, assuming that the returns follow skew geometric Brownian motions and that they are correlated, we describe some statistical properties for the ex-post, the ex-ante tracking errors, and the forecasted tracking portfolio. To this end, we develop an innovative statistical methodology, based on a benchmark-asset principal component factorization, to determine a tracking portfolio that replicates the performance of a benchmark by investing in a subset of the investable universe. This strategy, named hybrid Principal Component Analysis (hPCA), is applied both on normal and skew distributions. In the case of skew-normal returns, we propose a framework for calibrating the model parameters, based on the maximum likelihood estimation method. For testing and validation, we compare four alternative models for index tracking. The first two are based on the hPCA when returns are assumed to be normal or skew-normal. The third model adopts a standard optimization-based approach and the last one is used in the financial sector by some practitioners. For validation and testing, we present a thorough comparison of these strategies on real-world data, both in terms of performance and computational efficiency. A noticeable result is that, not only, the suggested lean PCA-based portfolio selection approach compares well versus cumbersome algorithms for optimization-based portfolios, but, also, it could provide a better service to the asset management industry. © 2022, CC BY.

关键词： Financial data processing

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Levelized Cost of Energy Optimization Method for the Dish Solar Thermal Power Generation System 15th

Levelized Cost of Energy Optimization Method for the Dish So...

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15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019

作者： Dang, Genye Su, Hongsheng Yue, Biao School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou China Experimental Teaching Center on Computer Science Lanzhou Jiaotong University Lanzhou China

ISBN: (纸本)9783030324551

In view of the high cost of power generation and the shortcomings of scale and industrialization of dish-Stirling optical thermal power station, the NSGA-II algorithm is proposed to optimize and analyze levelized cost of energy for dish solar thermal power generation system. The capacity and cost model of dish-Stirling thermal power generation system is established, and the influence of power station capacity, thermal storage medium and thermal storage time on the levelized cost of energy is analyzed by using NSGA-II genetic algorithm and particle swarm optimization. The results show that the larger the scale of power generation, the lower the levelized cost of energy, and the thermal storage medium and the thermal storage time have a greater impact on the levelized cost of energy. © Springer Nature Switzerland AG, 2020.

关键词： Particle swarm optimization (PSO)

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Development of a SPOC of computer Ethics for students of computer science degree 11

Development of a SPOC of Computer Ethics for students of Com...

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11th International Conference on Virtual Campus, JICV 2021

作者： García-Holgado, Alicia García-Peñalvo, Francisco J. Therón, Roberto Vázquez-Ingelmo, Andrea Gamazo, Adriana González-González, Carina S. Iranzo, Rosa María Gil Silveira, Ismar Frango Alier Forment, Marc IUCE University of Salamanca GRIAL Research Group Computer Science Department Salamanca Spain IUCE University of Salamanca GRIAL GRIAL Research Group Didactics Organization and Research Methods Department Salamanca Spain University Institute of Women's Studies Universidad de la Laguna Computer and Systems Engineering Department San Cristóbal de la Laguna Spain Universitat de Lleida Computer Science and Industrial Engineering Department Lleida Spain Universidade Presbiteriana Mackenzie Faculdade de Computação e Informática Sao Paulo Brazil BCN-SEER BarcelonaTech Department of Service and Information System Engineering Barcelona Spain

ISBN: (纸本)9781665437035

Technology brings different benefits to society and involves challenges and ethical dilemmas that must be considered during any technology development. In this sense, graduates must recognise the social, legal, ethical and cultural issues inherent to the discipline of computer science. However, there is a lack of integration of computer ethics in the computer science curriculum in Spanish universities. This work introduces a pilot experience to develop a Small Private Open Course (SPOC) to introduce computer ethics as an extracurricular activity in the Bachelor's Degree of computer Engineering at the University of Salamanca. © 2021 IEEE.

关键词： Engineering education

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Socialformer: Social Network Inspired Long Document Modeling for Document Ranking

arXiv

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arXiv 2022年

作者： Zhou, Yujia Dou, Zhicheng Yuan, Huaying Ma, Zhengyi Gaoling School of Artificial Intelligence Renmin University of China China School of Information Renmin University of China China College of Computer Science Nankai University China Beijing Key Laboratory of Big Data Management and Analysis Methods China

Utilizing pre-trained language models has achieved great success for neural document ranking. Limited by the computational and memory requirements, long document modeling becomes a critical issue. Recent works propose to modify the full attention matrix in Transformer by designing sparse attention patterns. However, most of them only focus on local connections of terms within a fixed-size window. How to build suitable remote connections between terms to better model document representation remains underexplored. In this paper, we propose the model Socialformer, which introduces the characteristics of social networks into designing sparse attention patterns for long document modeling in document ranking. Specifically, we consider several attention patterns to construct a graph like social networks. Endowed with the characteristic of social networks, most pairs of nodes in such a graph can reach with a short path while ensuring the sparsity. To facilitate efficient calculation, we segment the graph into multiple subgraphs to simulate friend circles in social scenarios. Experimental results confirm the effectiveness of our model on long document modeling. Copyright © 2022, The Authors. All rights reserved.

关键词： Search engines

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Dual-Weighted Multiview Clustering Based on Anchor

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Concurrency and Computation: Practice and Experience 2025年第15-17期37卷

作者： Yan Zhang Yali Peng Shengnan Wu Shigang Liu Key Laboratory of Modern Teaching Technology Ministry of Education Xi'an China School of Computer Science Shaanxi Normal University Xi'an China

In the field of multiview clustering, how to make full use of information from multiple data sources to improve the clustering performance has become a hot research topic. However, the rapid growth of high-dimensional multiview data brings great challenges to the research of multiview clustering algorithms, especially the time and space complexity of the algorithms. As an effective solution, anchor-based technique has gained wide attention in large-scale multiview clustering tasks. Nevertheless, the current anchor-based methods fail to fully take into account the importance of different views and the difference and diversity of anchors at the same time, which limits the clustering performance to some extent. To address these problems, we propose a dual-weighted multiview clustering based on anchor (DwMVCA). First, we effectively distinguish the different impacts of high-quality and low-quality views on clustering by adaptively learning the weights of different views. Second, by introducing the adaptive weighting matrix of anchors and self-correlation matrix regularization term, the difference and diversity of anchors are fully considered to effectively reduce the effect of redundant information on clustering. Furthermore, we design a three-step alternating optimization algorithm to solve the resultant optimization problem and prove its convergence. Extensive experimental results show that the proposed DwMVCA has obvious advantages in clustering performance on large-scale datasets, especially on datasets with more than 100,000 samples that still maintain linear time complexity.

关键词： anchor points multiview clustering subspace clustering weighting

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Turing pattern of a reaction-diffusion predator-prey model with weak Allee effect and delay

Turing pattern of a reaction-diffusion predator-prey model w...

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2020 International Conference on Physics, Mechanics and Mathematical science, PMMS 2020

作者： Li, Yexuan Liu, Hua Wei, Yumei Ma, Ming School of Mathematics and Computer Science Northwest Minzu University Lanzhou730000 China Experimental Teaching Department Northwest Minzu University Lanzhou730000 China

In this paper, we investigate a reaction-diffusion model with gestation delay and weak Allee effect. The conditions of delay-induced instability are obtained after stability analysis. By using numerical simulation, we discuss the effects of gestation delay and weak Allee effect on the Turing pattern. The results show that weak Allee effect and gestation delay can change the pattern formations. This means Allee effect and delay play significant roles in spatial invasion of populations. © Published under licence by IOP Publishing Ltd.

关键词： Diffusion in liquids

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