Results 11 to 20 of about 4,144,297 (347)
NEJM Evidence, 2023 Large Language ModelsIn the latest edition of Stats, STAT!, Fralick and colleagues explain the statistics behind large language models - used in chat bots like ChatGPT and Bard. While these new tools may seem remarkably intelligent, at their core they just assemble sentences based on statistics from large amounts of text.
Michael, Fralick +6 more
+7 more sources
Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning [PDF]
International Conference on Learning Representations, 2023 Large language models (LLMs) have demonstrated impressive reasoning abilities in complex tasks. However, they lack up-to-date knowledge and experience hallucinations during reasoning, which can lead to incorrect reasoning processes and diminish their ...
Linhao Luo +3 more
semanticscholar +1 more source
TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding [PDF]
Computer Vision and Pattern Recognition, 2023 This work proposes TimeChat, a time-sensitive multi-modal large language model specifically designed for long video understanding. Our model incorporates two key architectural contributions: (1) a timestamp-aware frame encoder that binds visual content ...
Shuhuai Ren +4 more
semanticscholar +1 more source
StructGPT: A General Framework for Large Language Model to Reason over Structured Data [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 In this paper, we study how to improve the zero-shot reasoning ability of large language models~(LLMs) over structured data in a unified way. Inspired by the study on tool augmentation for LLMs, we develop an \emph{Iterative Reading-then-Reasoning~(IRR)}
Jinhao Jiang +5 more
semanticscholar +1 more source
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models [PDF]
International Conference on Machine Learning, 2023 The cost of vision-and-language pre-training has become increasingly prohibitive due to end-to-end training of large-scale models. This paper proposes BLIP-2, a generic and efficient pre-training strategy that bootstraps vision-language pre-training from
Junnan Li +3 more
semanticscholar +1 more source
The Language Essence of the World: A Linguistic Interpretation of the Large Language Model
Computer Sciences & Mathematics Forum, 2023 The source of characters is hieroglyph. Hieroglyph is the imitation and reference of the phenomena and objects in the natural world. The objects and phenomena in the natural world are the original image.
Leiming Shi, Peng Wu
doaj +1 more source
Autoformalization with Large Language Models
Advances in Neural Information Processing Systems 35, 2022 Autoformalization is the process of automatically translating from natural language mathematics to formal specifications and proofs. A successful autoformalization system could advance the fields of formal verification, program synthesis, and artificial intelligence.
Wu, Yuhuai +6 more
openaire +4 more sources
A large language model for electronic health records [PDF]
npj Digital Medicine, 2022 There is an increasing interest in developing artificial intelligence (AI) systems to process and interpret electronic health records (EHRs). Natural language processing (NLP) powered by pretrained language models is the key technology for medical AI ...
Xi Yang +18 more
semanticscholar +1 more source
Risk Analysis and Response Strategies of Large Language Models for Security Governance [PDF]
中国工程科学To address the challenges of fragmented understanding of Large Language Model (LLM) security risks and the inadequacy of LLM risk classification and grading frameworks, this study aims to construct a comprehensive framework that integrates risk mechanism
Kun Jia +4 more
doaj +1 more source
Studying Large Language Model Generalization with Influence Functions [PDF]
arXiv.org, 2023 When trying to gain better visibility into a machine learning model in order to understand and mitigate the associated risks, a potentially valuable source of evidence is: which training examples most contribute to a given behavior?
R. Grosse +16 more
semanticscholar +1 more source