Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models

Exploring the application of powerful large language models (LLMs) on the fundamental named entity recognition (NER) task has drawn much attention recently. This work aims to investigate the possibilities of pushing the boundary of zero-shot NER with LLM via a training-free self-improving strategy. We propose a self-improving framework, which utilize an unlabeled corpus to stimulate the self-learning ability of LLMs on NER. First, we use LLM to make predictions on the unlabeled corpus and obtain the self-annotated data. Second, we explore various strategies to select reliable samples from the self-annotated dataset as demonstrations, considering the similarity, diversity and reliability of demonstrations. Finally, we conduct inference for the test query via in-context learning with the selected self-annotated demonstrations. Through comprehensive experimental analysis, our study yielded the following findings: (1) The self-improving framework further pushes the boundary of zero-shot NER with LLMs, and achieves an obvious performance improvement; (2) Iterative self-improving or naively increasing the size of unlabeled corpus does not guarantee improvements; (3) There might still be space for improvement via more advanced strategy for reliable entity selection

Aligning Large Language Models to a Domain-specific Graph Database

Graph Databases (Graph DB) are widely applied in various fields, including finance, social networks, and medicine. However, translating Natural Language (NL) into the Graph Query Language (GQL), commonly known as NL2GQL, proves to be challenging due to its inherent complexity and specialized nature. Some approaches have sought to utilize Large Language Models (LLMs) to address analogous tasks like text2SQL. Nevertheless, when it comes to NL2GQL taskson a particular domain, the absence of domain-specific NL-GQL data pairs makes it difficult to establish alignment between LLMs and the graph DB. To address this challenge, we propose a well-defined pipeline. Specifically, we utilize ChatGPT to create NL-GQL data pairs based on the given graph DB with self-instruct. Then, we use the created data to fine-tune LLMs, thereby achieving alignment between LLMs and the graph DB. Additionally, during inference, we propose a method that extracts relevant schema to the queried NL as the input context to guide LLMs for generating accurate GQLs.We evaluate our method on two constructed datasets deriving from graph DBs in finance domain and medicine domain, namely FinGQL and MediGQL. Experimental results demonstrate that our method significantly outperforms a set of baseline methods, with improvements of 5.90 and 6.36 absolute points on EM, and 6.00 and 7.09 absolute points on EX, respectively.Comment: 13 pages,2 figure

Information fusion in human eye aberration measurement

Abstract An information fusion method measuring human eye aberrations is presented here. We have built an optical setup to combine two systems which can measure the human eye's objective and subjective wavefront aberration separately. Then the result datum is fused on feature level by information fusion method. Finally, we have done a series of experiments to demonstrate this combined fusion method and give some discussions

Solar Ring Mission: Building a Panorama of the Sun and Inner-heliosphere

Solar Ring (SOR) is a proposed space science mission to monitor and study the Sun and inner heliosphere from a full 360{\deg} perspective in the ecliptic plane. It will deploy three 120{\deg}-separated spacecraft on the 1-AU orbit. The first spacecraft, S1, locates 30{\deg} upstream of the Earth, the second, S2, 90{\deg} downstream, and the third, S3, completes the configuration. This design with necessary science instruments, e.g., the Doppler-velocity and vector magnetic field imager, wide-angle coronagraph, and in-situ instruments, will allow us to establish many unprecedented capabilities: (1) provide simultaneous Doppler-velocity observations of the whole solar surface to understand the deep interior, (2) provide vector magnetograms of the whole photosphere - the inner boundary of the solar atmosphere and heliosphere, (3) provide the information of the whole lifetime evolution of solar featured structures, and (4) provide the whole view of solar transients and space weather in the inner heliosphere. With these capabilities, Solar Ring mission aims to address outstanding questions about the origin of solar cycle, the origin of solar eruptions and the origin of extreme space weather events. The successful accomplishment of the mission will construct a panorama of the Sun and inner-heliosphere, and therefore advance our understanding of the star and the space environment that holds our life.Comment: 41 pages, 6 figures, 1 table, to be published in Advances in Space Researc

A Real-Time Image Row-Compression Method for High-Definition USB Cameras Based on FPGA

A real-time image compression method based on field programmable gate array is proposed for the problem of high-frame-rate high-resolution camera image transmission under the limited bandwidth of universal serial bus (USB). This method quantizes image pixels on a per-row basis, taking advantage of the high correlation between adjacent pixels within a row, thus reducing the data volume of a single frame image transmission. The algorithm also aims to minimize the decoding complexity on the central processor of the receiving end. Corresponding hardware circuits and software programs are designed, and tests are conducted on an experimental platform. The experimental results show that this method effectively compresses image data losslessly on the board, improves the transmission frame rate. The maximum frame rate of $1280\times 1280$ images tested in a USB 2.0 environment can reach 25.58 fps, an improvement of 11.67 fps compared to the original data transfer, with a compression rate of up to 55.8%. Furthermore, this method outperforms PNG decoding in terms of decoding speed, supports multi-core decoding, and achieves the highest decoding speed of 61fps when tested on the $1920\times 1080$ image with 16 threads. This method provides a feasible transfer solution for real-time compressed transmission of high-speed and high-definition cameras in the industrial field

Nature of support plays vital roles in H2O promoted CO oxidation over Pt catalysts

Pt nanoparticle catalysts supported on a series of TiO2-SiO2 composites with different molar ratios were prepared, characterized, and their CO oxidation activities were evaluated under dry and humid condi-tions. Among the catalysts, Pt/1Ti-3Si showed the best performance under both conditions and potentials for future industrial applications. H218O experiments were designed and the CO2 composition was calcu-lated to quantify the promotion effect of H2O, which was highly correlated with the concentration of H2O and Ti-Si ratio. The XRD, XPS and BET results revealed that the defects on the supports inhibited phase transformation and lattice growth for anatase TiO2. These defects also led to an increase in the number of acid sites on Pt/TiO2-SiO2. The TEM, EDS mapping, and CO chemosorption results indicated that metal-lic Pt0 particles were formed, which was beneficial for CO oxidation during reaction. It was found that the generation of OH from H2O dissociation and the desorption of OH on TiO2 were much easier than those on SiO2, illustrating that the H2O promotion effect could be controlled by regulating the nature of support. The mechanism of H2O promotion was proposed by experimental and theoretical methods, which con-firmed the carboxyl intermediate pathway rather than the formate pathway.(c) 2022 Elsevier Inc. All rights reserved

Nature of support plays vital roles in H2O promoted CO oxidation over Pt catalysts

Pt nanoparticle catalysts supported on a series of TiO2-SiO2 composites with different molar ratios were prepared, characterized, and their CO oxidation activities were evaluated under dry and humid condi-tions. Among the catalysts, Pt/1Ti-3Si showed the best performance under both conditions and potentials for future industrial applications. H218O experiments were designed and the CO2 composition was calcu-lated to quantify the promotion effect of H2O, which was highly correlated with the concentration of H2O and Ti-Si ratio. The XRD, XPS and BET results revealed that the defects on the supports inhibited phase transformation and lattice growth for anatase TiO2. These defects also led to an increase in the number of acid sites on Pt/TiO2-SiO2. The TEM, EDS mapping, and CO chemosorption results indicated that metal-lic Pt0 particles were formed, which was beneficial for CO oxidation during reaction. It was found that the generation of OH from H2O dissociation and the desorption of OH on TiO2 were much easier than those on SiO2, illustrating that the H2O promotion effect could be controlled by regulating the nature of support. The mechanism of H2O promotion was proposed by experimental and theoretical methods, which con-firmed the carboxyl intermediate pathway rather than the formate pathway.(c) 2022 Elsevier Inc. All rights reserved

Behavioral Intention to Resist the Consumption of Wild Animals in China: Netizen Survey

Since the beginning of 2020, China has banned the consumption of wild animals to combat the spread of zoonoses. Most existing studies focus on the intention and behavior of wildlife consumption and their causes; however, few have looked at public willingness to resist wildlife consumption, as well as the cause and effects of such actions. In this study, a framework for an extended theory of planned behavior was constructed. Based on a 7-point Likert scale, a sample of 1194 respondents from eight provinces across China was obtained through an online survey. Structural equation modeling was used to analyze netizen behavioral intention to resist consuming wild animals and their causes to provide a reference for the implementation and optimization of relevant policies. The study model passed the goodness-of-fit test, confirming the robustness of the results. The results showed that Chinese netizens’ intention to resist consuming wild animals was moderate, with 55.19% willing to participate in activities against it, i.e., it is important to resist eating wild animals as a standard. Attitude, subjective norm, perceived behavioral control, and past experience of the Chinese netizen had significant positive effects on resistance intention, i.e., (1) netizens’ current living area with severe outbreaks were more likely to resist wildlife consumption, (2) highly knowledge level netizens were more likely to resist wildlife consumption than less knowledgeable ones, and (3) lower income level had higher behavioral intentions of netizens. The findings suggest that the government must take a lead role in wildlife protection and strengthen its restrictions, laws, and regulations. The media should also be used to promote conservation and popularize a protective message in favor of wild animals. Public quality and assurance of wildlife protection should be culturally reinforced to effectively ban the illegal trade of wild animals and their products