Domain Knowledge-Guided Self-Supervised Change Detection for Remote Sensing Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 As one of the most popular topics in the field of Earth observation using remote sensing images, change detection (CD) provides great practical and valuable significance for many fields.
Li Yan, Jianbing Yang, Jian Wang
doaj +2 more sources
ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge [PDF]
Cureus, 2023 Objective The primary aim of this research was to address the limitations observed in the medical knowledge of prevalent large language models (LLMs) such as ChatGPT, by creating a specialized language model with enhanced accuracy in medical advice ...
Yunxiang Li +5 more
semanticscholar +1 more source
SayCanPay: Heuristic Planning with Large Language Models using Learnable Domain Knowledge [PDF]
AAAI Conference on Artificial Intelligence, 2023 Large Language Models (LLMs) have demonstrated impressive planning abilities due to their vast "world knowledge". Yet, obtaining plans that are both feasible (grounded in affordances) and cost-effective (in plan length), remains a challenge, despite ...
Rishi Hazra +2 more
semanticscholar +1 more source
FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Models [PDF]
North American Chapter of the Association for Computational Linguistics, 2023 Large language models have demonstrated outstanding performance in various natural language processing tasks, but their security capabilities in the financial domain have not been explored, and their performance on complex tasks like financial agent ...
Liwen Zhang +13 more
semanticscholar +1 more source
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair [PDF]
International Conference on Software Engineering, 2023 Automated Program Repair (APR) improves soft-ware reliability by generating patches for a buggy program automatically. Recent APR techniques leverage deep learning (DL) to build models to learn to generate patches from existing patches and code corpora ...
Nan Jiang +5 more
semanticscholar +1 more source
Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models’ Memories [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 Pre-trained language models (PLMs) demonstrate excellent abilities to understand texts in the generic domain while struggling in a specific domain. Although continued pre-training on a large domain-specific corpus is effective, it is costly to tune all ...
Shizhe Diao +4 more
semanticscholar +1 more source
Knowledge Solver: Teaching LLMs to Search for Domain Knowledge from Knowledge Graphs [PDF]
arXiv.org, 2023 Large language models (LLMs), such as ChatGPT and GPT-4, are versatile and can solve different tasks due to their emergent ability and generalizability.
Chao Feng, Xinyu Zhang, Zichu Fei
semanticscholar +1 more source
Domain Knowledge Distillation from Large Language Model: An Empirical Study in the Autonomous Driving Domain [PDF]
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023 Engineering knowledge-based (or expert) systems require extensive manual effort and domain knowledge. As Large Language Models (LLMs) are trained using an enormous amount of cross-domain knowledge, it becomes possible to automate such engineering ...
Yun Tang +5 more
semanticscholar +1 more source
A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge. [PDF]
Sci Rep, 2023 Discovering a meaningful symbolic expression that explains experimental data is a fundamental challenge in many scientific fields. We present a novel, open-source computational framework called Scientist-Machine Equation Detector (SciMED), which ...
Keren LS, Liberzon A, Lazebnik T.
europepmc +3 more sources
Proceedings of the IEEE, 2021 As one of the key communication scenarios in the fifth-generation and also the sixth-generation (6G) mobile communication networks, ultrareliable and low-latency communications (URLLCs) will be central for the development of various emerging mission ...
Changyang She +6 more
semanticscholar +1 more source