MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization

1 code implementation • 24 Feb 2024 • Nguyen Do, Tanmoy Chowdhury, Chen Ling, Liang Zhao, My T. Thai

Multiplex influence maximization (MIM) asks us to identify a set of seed users such as to maximize the expected number of influenced users in a multiplex network.

Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey

no code implementations • 30 May 2023 • Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Dhagash Mehta, Stefano Pasquali, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Jian Pei, Carl Yang, Liang Zhao

In this article, we present a comprehensive survey on domain specification techniques for large language models, an emerging direction critical for large language model applications.

Chatbot Language Modelling +1

Knowledge-enhanced Neural Machine Reasoning: A Review

no code implementations • 4 Feb 2023 • Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao

Knowledge-enhanced neural machine reasoning has garnered significant attention as a cutting-edge yet challenging research area with numerous practical applications.

DeepGAR: Deep Graph Learning for Analogical Reasoning

1 code implementation • 19 Nov 2022 • Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, Liang Zhao

As the most well-known computational method of analogical reasoning, Structure-Mapping Theory (SMT) abstracts both target and base subjects into relational graphs and forms the cognitive process of analogical reasoning by finding a corresponding subgraph (i. e., correspondence) in the target graph that is aligned with the base graph.

Graph Learning