22 papers · ranked by Valyu relevance
Ciyuan Peng, Feng Xia, Mehdi Naseriparsa, Francesco Osborne
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately. As graph data, knowledge graphs accumulate and convey knowledge of the real world. It has been well-recognized that knowledge graphs…
Xintao Wang, Qianwen Yang, Yongting Qiu, Jiaqing Liang + 4 more
'Zhouhong Gu' 'Yanghua Xiao' 'Wei Wang'] Large language models (LLMs) have demonstrated impressive impact in the field of natural language processing, but they still struggle with several issues regarding, such as completeness, timeliness, faithfulness and adaptability. While recent efforts have focuses on connecting…
Wenjing Yao, Ning Li
English has become an important tool for China's opening to the outside world and exchanges with other countries. More and more people have the motivation and requirements to learn English, but under the traditional English learning mode and traditional teaching mode, the cultivation of learners' autonomous learning…
Shaked Launer-Wachs, Hillel Taub-Tabib, Yoav Goldberg, Yosi Shamay
As knowledgebases become increasingly important for structuring vast amounts of scientific knowledge and making it accessible to researchers, their construction entails expensive multi-year projects involving teams of bio-curators, computer scientists, or both. This restricts the coverage of existing knowledgebases to…
Matt Beton, Simran Chana, Simran Chana
The mammalian brain has developed a solution to a problem that current AI architectures are yet to solve: storing specific episodic facts without corrupting general semantic knowledge. Neuroscience explains this capacity through Complementary Learning Systems theory, which posits that biological memory requires two…
Zhangyin Feng, Weitao Ma, YU Wei-jiang, Lei Huang + 6 more
'Qianglong Chen' 'Weihua Peng' 'Xiaocheng Feng' 'Bing Qin' 'Ting Liu'] Large language models (LLMs) exhibit superior performance on various natural language tasks, but they are susceptible to issues stemming from outdated data and domain-specific limitations. In order to address these challenges, researchers have…
Authors not listed
Large language models (LLMs) have garnered increasing attention owing to their potential as collaborative assistants in scientific studies. However, adapting an LLM to specialized domains remains challenging because of the difficulty in incorporating domain-specific knowledge. In the present study, we propose a…
Yuan Zhang, Feng Pan, Xin Sui, Kaixian Yu + 15 more
To cope with the rapid growth of scientific publications and data in biomedical research, knowledge graphs (KGs) have emerged as a powerful data structure for integrating large volumes of heterogeneous data to facilitate accurate and efficient information retrieval and automated knowledge discovery (AKD). However…
Authors not listed
The interdisciplinary nature of redox flow batteries (RFBs), spanning chemistry, materials, and engineering, has led to a vast and fragmented body of research, hindering the efficient synthesis of knowledge. An intelligent question-answering system is there-fore essential to organize this dispersed knowledge, enhance…
Amy Xin, Jinxin Liu, Zijun Yao, Z. -Y. Lee + 3 more
Knowledge Reasoning Authors: ['Amy Xin' 'Jinxin Liu' 'Zijun Yao' 'Z. -Y. Lee' 'Shulin Cao' 'Lei Hou' 'Juanzi Li'] Recent advancements in large language models (LLMs) have led to significant improvements in various natural language processing tasks, but it is still challenging for LLMs to perform knowledgeintensive…
Li Zhang, Xiaoran Yang, Shijian Li, Tianyi Liao + 1 more
Background Medical information has rapidly increased on the internet and has become one of the main targets of search engine use. However, medical information on the internet is subject to the problems of quality and accessibility, so ordinary users are unable to obtain answers to their medical questions conveniently.…
Authors not listed
Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
Guangrong Qin, Kamileh Narsinh, Qi Wei, Jared C. Roach + 15 more
As large clinical and multiomics datasets and knowledge resources accumulate, they need to be transformed into computable and actionable information to support automated reasoning. These datasets range from laboratory experiment results to electronic health records (EHRs). Barriers to accessibility and sharing of such…
Authors not listed
We have developed Aitomia – a platform powered by AI to assist in performing AI-driven atomistic and quantum chemical (QC) simulations. This evolving intelligent assistant platform is equipped with chatbots and AI agents to help experts and guide non-experts in setting up and running atomistic simulations, monitoring…
Haihua Lu, Liang Yu, Yantao He, Liwei Tian + 1 more
Information retrieval serves as a critical methodology for accurately and efficiently obtaining the required information from massive amounts of data. In this paper, we propose an information retrieval framework (SE-MSLC) that utilizes information theory to improve the retrieval effectiveness of inverted index…
Khalid Rasheed Memon, Bilqees Ghani, Syed Irfan Hyder, Heesup Han + 3 more
'Muhammad Zada' 'Antonio Ariza-Montes' 'Marcelo Arraño-Muñoz'] The fourth industrial revolution will be ushered in by future high technology, and as a result, the world will face new difficulties relating to people, the environment, and profitability. Accordingly, the competitive edge and long-term viability of…
Mayla R. Boguslav, Nourah M. Salem, Elizabeth K. White, Katherine J. Sullivan + 5 more
Research progresses through the process of making the unknown unknowns into known unknowns, then into knowns. Many knowledge-bases exist to capture the knowns and can be used by graduate students to explore a topic or help researchers contextualize experimental results using concept enrichment methods. The unknowns…
Yihua Cheng, Kuntai Du, Jiayi Yao, Junchen Jiang
As the use of large language models (LLMs) expands rapidly, so does the range of knowledge needed to supplement various LLM queries. Thus, enabling modular and efficient injection of new knowledge in LLM inference is critical. We argue that compared to the more popular fine-tuning and incontext learning, using KV…
Boxi Cao, Hongyu Lin, Xianpei Han, Le Sun
Knowledge plays a critical role in artificial intelligence. Recently, the extensive success of pre-trained language models (PLMs) has raised significant attention about how knowledge can be acquired, maintained, updated and used by language models. Despite the enormous amount of related studies, there still lacks a…
Jennifer H. Coane, John Cipollini, Talia E. Barrett, Joshua Kavaler + 1 more
'Sharda Umanath'] The present study examined how lay participants define the following concepts used widely in psychology: being intelligent, knowing, and remembering. In the scientific community, knowledge overlaps with the contents of semantic memory, crystallized intelligence reflects the accumulation of knowledge…
Kazunori D Yamada
Artificial intelligence that accumulates knowledge and presents it to users has the potential to become a vital ally for humanity. It is thought to be advantageous for such artificial intelligence to have the capability to continually accumulate knowledge while operating, as opposed to needing to relearn each time new…
Authors not listed
Step-by-step thinking is essential in all domains of chemical sciences and engineering. While machine learning tools are broadly used, algorithms that automate reasoning are far less common. We elaborate on seven categories of human reasoning activities and connect each to applications in chemical science and…