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Entity-Aware Multimodal Alignment Framework for News Image Captioning
Junzhe Zhang, Huixuan Zhang, Xiaojun Wan
https://arxiv.org/abs/2402.19404 https://

Entity-Aware Multimodal Alignment Framework for News Image Captioning
News image captioning task is a variant of image captioning task which requires model to generate a more informative caption with news image and the associated news article. Multimodal Large Language models have developed rapidly in recent years and is promising in news image captioning task. However, according to our experiments, common MLLMs are not good at generating the entities in zero-shot setting. Their abilities to deal with the entities information are still limited after simply fine-t…

This https://arxiv.org/abs/2312.05626 has been replaced.
link: https://scholar.google.com/scholar?q=a

Redefining Developer Assistance: Through Large Language Models in Software Ecosystem
In this paper, we delve into the advancement of domain-specific Large Language Models (LLMs) with a focus on their application in software development. We introduce DevAssistLlama, a model developed through instruction tuning, to assist developers in processing software-related natural language queries. This model, a variant of instruction tuned LLM, is particularly adept at handling intricate technical documentation, enhancing developer capability in software specific tasks. The creation of De…

Which Virus Will Cause the Next Global #Pandemic? Scientists Discover New Disease X Clues
https://scitechdaily.com/which-virus-w

Which Virus Will Cause the Next Global Pandemic? Scientists Discover New Disease X Clues
Understanding the ancestry of virus families may assist researchers in pinpointing which variants possess the potential to become Disease X, the elusive pathogen responsible for the next worldwide pandemic. A study has identified 70 virus lineages – groups of related viruses – that pose the bigge

This https://arxiv.org/abs/2312.05626 has been replaced.
link: https://scholar.google.com/scholar?q=a

Redefining Developer Assistance: Through Large Language Models in Software Ecosystem
In this paper, we delve into the advancement of domain-specific Large Language Models (LLMs) with a focus on their application in software development. We introduce DevAssistLlama, a model developed through instruction tuning, to assist developers in processing software-related natural language queries. This model, a variant of instruction tuned LLM, is particularly adept at handling intricate technical documentation, enhancing developer capability in software specific tasks. The creation of De…

This https://arxiv.org/abs/2312.13521 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

Preparing to Integrate Generative Pretrained Transformer Series 4 models into Genetic Variant Assessment Workflows: Assessing Performance, Drift, and Nondeterminism Characteristics Relative to Classifying Functional Evidence in Literature
Background. Large Language Models (LLMs) hold promise for improving genetic variant literature review in clinical testing. We assessed Generative Pretrained Transformer 4's (GPT-4) performance, nondeterminism, and drift to inform its suitability for use in complex clinical processes. Methods. A 2-prompt process for classification of functional evidence was optimized using a development set of 45 articles. The prompts asked GPT-4 to supply all functional data present in an article related to a v…