[目的/意义]旨在对比分析学者撰写的图书馆信息素养教育论文引言与GPT-4生成引言的异同,并探讨其对图书馆AI素养教育的启示.[方法/过程]对比96篇高被引论文的学者撰写引言与GPT-4生成的引言,利用机器学习分类方法和内容分析技术,深入探讨两者在语言表达,逻辑结构,信息准确性等方面的异同.[结果/结论]学者撰写的引言与GP...
import random OPTIONS = ["rock", "paper", "scissors"] def get_computer_choice():return random.choice(OPTIONS) def get_player_choice():while True:choice = input("Enter your choice (rock, paper, scissors): ").lower()if choice in OPTIONS:return choice def check_winner(player, computer):...
Mini-Gemini还提供了2B小杯到34B的超大杯,最强模型在多个指标上相比Google Gemini Pro甚至GPT-4V都不遑多让。目前,Mini-Gemini从代码、模型、到数据已全部开源,登上了PaperWithCode热榜。 Mini-Gemini线上Demo也已发布,超会玩梗,一起...
🎞️ Project Page 📝 arXiv Paper Overview Most current LLM-based models for video understanding can process videos within minutes but struggle with processing lengthy videos due to the “noise and redundancy challenge” and “memory and compu- tation” challenges. In this paper, we present...
- 图片类型:示意图、折线图、地图、照片、几何图形等12种;目前多模态大模型在该榜单上的正确率都低于50%,GPT4-V最高为48.1%。Paper:链接Github: 链接#LLM(大型语言模型) #多模态大模型 #评测 #AIGC 发布于 2024-02-28 17:39・IP 属地日本 赞同15 分享收藏 ...
Please check out the paper"On the Hidden Mystery of OCR in Large Multimodal Models", where LLaVA consistently outperforms miniGPT4 on 17 out of 18 datasets, despite LlaVA being trained with an order of magnitude smaller training data. ...
Your goal is to ensure that the user can easily understand the content of the paper and continue their learning journey.The first sentence you say to the user should be "我是你的论文解析老师,请给我论文PDF文件" 好的,我们开始对YOLOv10的论文进行详细解析和翻译。
🐱 NVLM 1.0能够理解复杂多模态幽默,例如“abstract vs. paper”迷因。 数智朋克消息,Nvidia发布了多模态大型语言模型NVLM 1.0,旨在与封闭的GPT-4o及开源的Llama 3-V 405B、InternVL 2等竞争。NVLM 1.0不仅开源了模型权重,还提供了基于Megatron-Core框架的程序代码,展现了其对AI研究与应用的贡献。
In this paper, we establish a benchmark named HalluQA (Chinese Hallucination Question-Answering) to measure the hallucination phenomenon in Chinese large l... Q Cheng,T Sun,W Zhang,... 被引量: 0发表: 2023年 走向野已知之未知冶院GPT 大语言模型助力 实现以人为本的信息检索 [Purpose/Significanc...
地址: githubcom/kaixindelele/ChatPaper 10、MLX 简介: MLX是一个为苹果硅芯片设计的数组框架,专注于利用Apple Silicon的硬件特性,提供高性能的机器学习运算能力,旨在优化和加速机器学习任务在苹果硬件上的执行效率。 地址: githubcom/ml-explore/mlx#人工智能#AI技术#AI绘画#LLM(大型语言模型)#机器学习#矩阵运算#...