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Editorial for Special Issue on Large-scale Pre-training:Data,Models,and Fine-tuning

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Machine Intelligence Research 2023年第2期20卷 145-146页

作者： ji-rong wen ji-rong wen Zi Huang Hanwang Zhang Renmin University of China China Zi Huang The University of QueenslandAustralia Hanwang Zhang Nanyang Technological UniversitySingapore Renmin University of China China The University of Queensland Australia Nanyang Technological University Singapore

In recent years,there has been a surge of interest and rapid development in large-scale pre-training due to the explosive growth of both data and model ***-scale training has achieved impressive performance milestones across a wide range of practical problems,including natural language processing,computer vision,recommendation systems,robotics,and other basic research areas like bioinformatics.

关键词： computer scale parameters

DynamicRetriever:A Pre-trained Model-based IR System Without an Explicit Index

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Machine Intelligence Research 2023年第2期20卷 276-288页

作者： Yu-jia Zhou jing Yao Zhi-Cheng Dou Ledell Wu ji-rong wen Gaoling School of Artificial Intelligence Renmin University of ChinaBeijing 100872China Beijing Academy of Artificial Intelligence Beijing 100084China

Web search provides a promising way for people to obtain information and has been extensively *** the surge of deep learning and large-scale pre-training techniques,various neural information retrieval models are proposed,and they have demonstrated the power for improving search(especially,the ranking)*** these existing search methods follow a common paradigm,i.e.,index-retrieve-rerank,where they first build an index of all documents based on document terms(i.e.,sparse inverted index)or representation vectors(i.e.,dense vector index),then retrieve and rerank retrieved documents based on the similarity between the query and documents via ranking *** this paper,we explore a new paradigm of information retrieval without an explicit index but only with a pre-trained ***,all of the knowledge of the documents is encoded into model parameters,which can be regarded as a differentiable indexer and optimized in an end-to-end ***,we propose a pre-trained model-based information retrieval(IR)system called DynamicRetriever,which directly returns document identifiers for a given *** such a framework,we implement two variants to explore how to train the model from scratch and how to combine the advantages of dense retrieval *** with existing search methods,the model-based IR system parameterizes the traditional static index with a pre-training model,which converts the document semantic mapping into a dynamic and updatable *** experiments conducted on the public search benchmark Microsoft machine reading comprehension(MS MARCO)verify the effectiveness and potential of our proposed new paradigm for information retrieval.

关键词： Information retrieval(IR) document retrieval model-based IR pre-trained language model differentiable search index

Generating timeline summaries with social media attention

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Frontiers of Computer Science 2016年第4期10卷 702-716页

作者： Wayne Xin ZHAO ji-rong wen Xiaoming LI School of Information Renmin University of China Beijing 100872 China Beijing Key Laboratory of Big Data Management and Analysis Methods Renmin University of China Beijing 100872 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data Beijing 100144 China

Timeline generation is an important research task which can help users to have a quick understanding of the overall evolution of one given topic. Previous methods simply split the time span into fixed, equal time intervals without studying the role of the evolutionary patterns of the underlying topic in timeline generation. In addition, few of these methods take users＇ collective interests into considerations to generate timelines. We consider utilizing social media attention to address these two problems due to the facts： 1） social media is an important pool of real users＇ collective interests; 2） the information cascades generated in it might be good indicators for boundaries of topic phases. Employing Twitter as a basis, we propose to incorporate topic phases and user＇s collective interests which are learnt from social media into a unified timeline generation algorithm. We construct both one informativeness-oriented and three interestingness-oriented evaluation sets over five topics. We demonstrate that it is very effective to generate both informative and interesting timelines. In addition, our idea naturally leads to a novel presen- tation of timelines, i.e., phase based timelines, which can potentially improve user experience.

关键词： timeline social media attention phase users'collective interests

Ranking and tagging bursty features in text streams with context language models

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Frontiers of Computer Science 2017年第5期11卷 852-862页

作者： Wayne Xin ZHAO Chen LIU ji-rong wen Xiaoming LI School of Information Renmin University of China Beijing 100872 China Beijing Key Laboratory of Big Data Management and Analysis Methods Renmin University of China Beijing 100872 China Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data Beijing 100144 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

Detecting and using bursty pattems to analyze text streams has been one of the fundamental approaches in many temporal text mining applications. So far, most existing studies have focused on developing methods to detect bursty features based purely on term frequency changes. Few have taken the semantic contexts of bursty features into consideration, and as a result the detected bursty features may not always be interesting and can be hard to interpret. In this article, we propose to model the contexts of bursty features using a language modeling approach. We propose two methods to estimate the context language models based on sentence-level context and document-level context. We then propose a novel topic diversity-based metric using the context models to find newsworthy bursty features. We also propose to use the context models to automatically assign meaningful tags to bursty features. Using a large corpus of news articles, we quantitatively show that the proposed context language models for bursty features can effectively help rank bursty features based on their newsworthiness and to assign meaningful tags to annotate bursty features. We also use two example text mining applications to qualitatively demonstrate the usefulness of bursty feature ranking and tagging.

关键词： bursty features bursty features ranking bursty feature tagging context modeling

Lead-free perovskite Cs_(2)AgBiBr_(6)photodetector detecting NIR light driven by titanium nitride plasmonic hot holes

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Photonics Research 2024年第3期12卷 522-533页

作者： ZIjiAN LIU YUYING XI wenBO ZENG TING ji wenYAN WANG SITONG GUO LINLIN SHI rong wen YANXIA CUI GUOHUI LI College of Physics College of Electronic Information and Optical EngineeringKey Laboratory of Advanced Transducers and Intelligent Control System of Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030032China

Lead-free perovskite Cs_(2)AgBiBr_(6)manifests great potential in developing high-performance,environmentally friendly,solution-processable photodetectors(PDs).However,due to the relatively large energy bandgap,the spectrum responses of Cs_(2)AgBiBr_(6)PDs are limited to the ultraviolet and visible region with wavelengths shorter than 560 *** this work,a broadband Cs_(2)AgBiBr_(6)PD covering the ultraviolet,visible,and near infrared(NIR)range is demonstrated by incorporating titanium nitride(TiN)nanoparticles that are prepared with the assistance of self-assembled polystyrene sphere *** addition,an atomically thick Al2O3layer is introduced at the interface between the Cs_(2)AgBiBr_(6)film and TiN nanoparticles to alleviate the dark current deterioration caused by nanoparticle *** a result,beyond the spectrum range where Cs_(2)AgBiBr_(6)absorbs light,the external quantum efficiency(EQE)of the TiN nanoparticle incorporated Cs_(2)AgBiBr_(6)PD is enhanced significantly compared with that of the control,displaying enhancement factors as high as 2000 over a broadband NIR wavelength *** demonstrated enhancement in EQE arises from the photocurrent contribution of plasmonic hot holes injected from TiN nanoparticles into Cs_(2)AgBiBr_(6).This work promotes the development of broadband solution-processable perovskite PDs,providing a promising strategy for realizing photodetection in the NIR region.

关键词： perovskite titanium ultraviolet

Impact of Carbon Chain Structures in the Backbone on the Flexibility of Modified Polyarylene Sulfide Resins: Molecular Dynamics Simulations and Mesoscopic Analysis

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Chinese Journal of Polymer Science 2024年第4期42卷 544-557页

作者： Chi Zhang rong Liu jing-Yuan Liu wen-Wei jiang Key Laboratory of Fine Chemical Engineering and Functional Materials School of Chemical EngineeringSichuan UniversityChengdu610065China

In the domain of high-performance engineering polymers, the enhancement of mechanical flexibility in poly(phenylene sulfide) (PPS) resins has long posed a significant challenge. A novel molecular structure, designated as PP-He-IS, wherein imide rings and an aliphatic hexylene chain are covalently incorporated into the PPS backbone to enhance its flexibility, is introduced in this study. Molecular dynamics (MD) simulations are employed to systematically explore the effects of diversifying the backbone chain structures by substituting phenyl units with alkyl chains of varying lengths, referred to as PP-A-IS where “A” signifies the distinct intermediary alkyl chain configurations. Computational analyses reveal a discernable decrement in the glass transition temperature (Tg) and elastic modulus, counterbalanced by an increment in yield strength as the alkyl chain length is extended. Notably, the PP-He-IS variant is shown to exhibit superior yield strength while simultaneously maintaining reduced elastic modulus and Tg values, positioning it as an advantageous candidate for flexible PPS applications. Mesoscopic analyses further indicate that structures such as PP-He-IS, PP-Pe-IS, and PP-Bu-IS manifest remarkable flexibility, attributable to the presence of freely rotatable carbon-carbon single bonds. Experimental validation confirms that a melting temperature of 504 K which is lower than that of conventional PPS, and lower crystallinity are exhibited by PP-He-IS, thereby affording enhanced processability without compromising inherent thermal stability. Novel insights into the strategic modification of PPS for mechanical flexibility are thus furnished by this study, which also accentuates the pivotal role played by molecular dynamics simulations in spearheading high-throughput investigations in polymer material modifications.

关键词： Molecular dynamics simulations Polyarylene Sulfide Main-chain modifications Flexibility Aliphatic hexylene chain

Dynamic Shortest Path Monitoring in Spatial Networks

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Journal of Computer Science & Technology 2016年第4期31卷 637-648页

作者： Shuo Shang Lisi Chen Zhe-Wei Wei Dan-Huai Guo ji-rong wen State Key Laboratory of Software Development Environment Beijing 100191 China Department of Computer Science China University of Petroleum Beijing 102249 China School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore Beijing Key Laboratory of Big-Data Management and Analysis Methods Renmin University of China Beijing 100080 China Computer Network Information Center Chinese Academy of Sciences Beijing 100190 China

With the increasing availability of real-time traffic information, dynamic spatial networks are pervasive nowa- days and path planning in dynamic spatial networks becomes an important issue. In this light, we propose and investigate a novel problem of dynamically monitoring shortest paths in spatial networks （DSPM query）. When a traveler aims to a des- tination, his/her shortest path to the destination may change due to two reasons： 1） the travel costs of some edges have been updated and 2） the traveler deviates from the pre-planned path. Our target is to accelerate the shortest path computing in dynamic spatial networks, and we believe that this study may be useful in many mobile applications, such as route planning and recommendation, car navigation and tracking, and location-based services in general. This problem is challenging due to two reasons： 1） how to maintain and reuse the existing computation results to accelerate the following computations, and 2） how to prune the search space effectively. To overcome these challenges, filter-and-refinement paradigm is adopted. We maintain an expansion tree and define a pair of upper and lower bounds to prune the search space. A series of optimization techniques are developed to accelerate the shortest path computing. The performance of the developed methods is studied in extensive experiments based on real spatial data.

关键词： shortest path dynamic spatial network spatial database location-based service

An Experimental Study of Text Representation Methods forCross-Site Purchase Preference Prediction Using the Social Text Data

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Journal of Computer Science & Technology 2017年第4期32卷 828-842页

作者： Ting Bai Hong-jian Dou Xin Zhao Ding-Yi Yang ji-rong wen School of Information Renmin University of China Beijing 100872 China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing 100872 China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou 510006 China

Nowadays, many e-commerce websites allow users to login with their existing social networking accounts. When a new user comes to an e-commerce website, it is interesting to study whether the information from external social media platforms can be utilized to alleviate the cold-start problem. In this paper, we focus on a specific task on cross-site information sharing, i.e., leveraging the text posted by a user on the social media platform (termed as social text) to infer his/her purchase preference of product categories on an e-commerce platform. To solve the task, a key problem is how to effectively represent the social text in a way that its information can be utilized on the e-commerce platform. We study two major kinds of text representation methods for predicting cross-site purchase preference, including shallow textual features and deep textual features learned by deep neural network models. We conduct extensive experiments on a large linked dataset, and our experimental results indicate that it is promising to utilize the social text for predicting purchase preference. Specially, the deep neural network approach has shown a more powerful predictive ability when the number of categories becomes large.

关键词： social media e-commerce website purchase preference deep neural network

Morphology Study for GeV Emission of Nearby Supernova Remnant G332.5-5.6

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Research in Astronomy and Astrophysics 2024年第4期24卷 134-140页

作者： Ming-Hong Luo Qing-wen Tang Xiu-rong Mo Department of Physics School of Physics and Materials ScienceNanchang UniversityNanchang 330031China

A spatial template is important to study nearby supernova remnants(SNRs).For SNR G332.5-5.6,we report a Gaussian disk with a radius of about 1°.06 to be a potential good spatial model in the γ-ray *** this new Gaussian disk,its GeV lightcurve shows a significant variability of about seven *** γ-ray observations of this SNR could be explained well either by a leptonic model or a hadronic model,in which a flat spectrum for the ejected electrons/protons is required.

关键词： ISM:supernova remnants gamma rays:ISM