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The potential of Large Language Models in language education
Освітній вимір, 2021 This editorial explores the potential of Large Language Models (LLMs) in language education. It discusses the role of LLMs in machine translation, the concept of ‘prompt programming’, and the inductive bias of LLMs for abstract textual reasoning.
Vita A. Hamaniuk
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Unifying Large Language Models and Knowledge Graphs: A Roadmap [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2023 Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the field of natural language processing and artificial intelligence, due to their emergent ability and generalizability. However, LLMs are black-box models, which often fall
Shirui Pan +5 more
semanticscholar +1 more source
GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts [PDF]
arXiv.org, 2023 Large language models (LLMs) have recently experienced tremendous popularity and are widely used from casual conversations to AI-driven programming.
Jiahao Yu +3 more
semanticscholar +1 more source
Enhancing Agriculture QA Models Using Large Language Models [PDF]
BIO Web of ConferencesAgriculture is a complex process that requires a great deal of knowledge and experience. Yet, the complexity and often chaotic nature of web data presents a considerable challenge in obtaining suitable results.
He Xiaoyan
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JMIR Medical Education, 2023 Background Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that can generate conversation-style responses to user input.
Aidan Gilson +6 more
semanticscholar +1 more source
LLM-Pruner: On the Structural Pruning of Large Language Models [PDF]
Neural Information Processing Systems, 2023 Large language models (LLMs) have shown remarkable capabilities in language understanding and generation. However, such impressive capability typically comes with a substantial model size, which presents significant challenges in both the deployment ...
Xinyin Ma, Gongfan Fang, Xinchao Wang
semanticscholar +1 more source
Language Models for Everyone—Responsible and Transparent Development of Open Large Language Models
Computer Sciences & Mathematics Forum, 2023 Large language and multimodal models are revolutionising many aspects of human work and creativity, with broad potential not only as chatbots and for information retrieval but as interaction points and integrators of large technical systems.
Daniel Gillblad
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Creating a large language model of a philosopher
Mind & Language, 2023 Can large language models produce expert‐quality philosophical texts? To investigate this, we fine‐tuned GPT‐3 with the works of philosopher Daniel Dennett. To evaluate the model, we asked the real Dennett 10 philosophical questions and then posed the same questions to the language model, collecting four responses for each question without cherry ...
Eric Schwitzgebel +2 more
openaire +2 more sources
Well‐being on supportive techniques in amyotrophic lateral sclerosis: from neurologists' perspective
Annals of Clinical and Translational Neurology, Volume 9, Issue 12, Page 1874-1883, December 2022., 2022 Abstract Objective To investigate intercultural neurologists' perception of well‐being in patients with amyotrophic lateral sclerosis (ALS) using gastrostomy (PEG), non‐invasive, and/or invasive ventilation (NIV/IV) and to analyse the determinants and impact on the management of the above medical interventions (MIs).
Krzysztof Barć +7 more
wiley +1 more source
Augmenting interpretable models with large language models during training
Nature Communications, 2023 Recent large language models (LLMs), such as ChatGPT, have demonstrated remarkable prediction performance for a growing array of tasks. However, their proliferation into high-stakes domains and compute-limited settings has created a burgeoning need for ...
Chandan Singh +3 more
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