Bioinformatics and biomedical informatics with ChatGPT: Year one review

J Wang, Z Cheng, Q Yao, L Liu, D Xu… - Quantitative Biology, 2024 - Wiley Online Library
The year 2023 marked a significant surge in the exploration of applying large language
model chatbots, notably Chat Generative Pre‐trained Transformer (ChatGPT), across …

Surveying the mllm landscape: A meta-review of current surveys

M Li, K Chen, Z Bi, M Liu, B Peng, Q Niu, J Liu… - arxiv preprint arxiv …, 2024 - arxiv.org
The rise of Multimodal Large Language Models (MLLMs) has become a transformative force
in the field of artificial intelligence, enabling machines to process and generate content …

Crud-rag: A comprehensive chinese benchmark for retrieval-augmented generation of large language models

Y Lyu, Z Li, S Niu, F **ong, B Tang, W Wang… - ACM Transactions on …, 2024 - dl.acm.org
Retrieval-Augmented Generation (RAG) is a technique that enhances the capabilities of
large language models (LLMs) by incorporating external knowledge sources. This method …

C-ICL: contrastive in-context learning for information extraction

Y Mo, J Liu, J Yang, Q Wang, S Zhang, J Wang… - arxiv preprint arxiv …, 2024 - arxiv.org
There has been increasing interest in exploring the capabilities of advanced large language
models (LLMs) in the field of information extraction (IE), specifically focusing on tasks related …

Editing factual knowledge and explanatory ability of medical large language models

D Xu, Z Zhang, Z Zhu, Z Lin, Q Liu, X Wu, T Xu… - Proceedings of the 33rd …, 2024 - dl.acm.org
Model editing aims to precisely alter the behaviors of large language models (LLMs) in
relation to specific knowledge, while leaving unrelated knowledge intact. This approach has …

An Autoregressive Text-to-Graph Framework for Joint Entity and Relation Extraction

U Zaratiana, N Tomeh, P Holat… - Proceedings of the AAAI …, 2024 - ojs.aaai.org
In this paper, we propose a novel method for joint entity and relation extraction from
unstructured text by framing it as a conditional sequence generation problem. In contrast to …

Llm4msr: An llm-enhanced paradigm for multi-scenario recommendation

Y Wang, Y Wang, Z Fu, X Li, W Wang, Y Ye… - Proceedings of the 33rd …, 2024 - dl.acm.org
As the demand for more personalized recommendation grows and a dramatic boom in
commercial scenarios arises, the study on multi-scenario recommendation (MSR) has …

Dreamdissector: Learning disentangled text-to-3d generation from 2d diffusion priors

Z Yan, J Zhou, F Meng, Y Wu, L Qiu, Z Ye, S Cui… - … on Computer Vision, 2024 - Springer
Text-to-3D generation has recently seen significant progress. To enhance its practicality in
real-world applications, it is crucial to generate multiple independent objects with …

Enhancing question answering for enterprise knowledge bases using large language models

F Jiang, C Qin, K Yao, C Fang, F Zhuang, H Zhu… - … on Database Systems …, 2024 - Springer
Efficient knowledge management plays a pivotal role in augmenting both the operational
efficiency and the innovative capacity of businesses and organizations. By indexing …

Large language models meet nlp: A survey

L Qin, Q Chen, X Feng, Y Wu, Y Zhang, Y Li… - arxiv preprint arxiv …, 2024 - arxiv.org
While large language models (LLMs) like ChatGPT have shown impressive capabilities in
Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this …