www.bing.com/ck/a?!&&p=97ec917a6a6afdd6cee43bf24cbdbdf7d6d9edb1afbe7f1104bb98a37635004aJmltdHM9MTc3MjU4MjQwMA&ptn=3&ver=2&hsh=4&fclid=2d19b174-a17d-65fa-0a3b-a667a07f64a5&u=a1aHR0cHM6Ly9henVyZS5taWNyb3NvZnQuY29tL2VuLXVzL3Jlc291cmNlcy9jbG91ZC1jb21wdXRpbmctZGljdGlvbmFyeS93aGF0LWFyZS1sYXJnZS1sYW5ndWFnZS1tb2RlbHMtbGxtcz9tc29ja2lkPTJkMTliMTc0YTE3ZDY1ZmEwYTNiYTY2N2EwN2Y2NGE1&ntb=1
LLM meaning Large language models (LLMs) are advanced AI systems that understand and generate natural language, or human-like text, using the data theyâve been trained on through machine â¦
arxiv.org/abs/2312.13951v1
Typhoon is a series of Thai large language models (LLMs) developed specifically for the Thai language. This technical report presents challenges and insights in developing Thai LLMs, including data preparation, pretraining, instruction-tuning, and ev...
arxiv.org/abs/2406.13677v3
Large language models (LLMs) often inherit and amplify social biases embedded in their training data. A prominent social bias is gender bias. In this regard, prior work has mainly focused on gender stereotyping bias - the association of specific role...
arxiv.org/abs/2310.09536v1
Large language models (LLMs) have demonstrated remarkable performance by following natural language instructions without fine-tuning them on domain-specific tasks and data. However, leveraging LLMs for domain-specific question answering suffers from...
arxiv.org/abs/2204.08096v3
This article presents a synthetic distracted driving (SynDD2 - a continuum of SynDD1) dataset for machine learning models to detect and analyze drivers' various distracted behavior and different gaze zones. We collected the data in a stationary vehic...
arxiv.org/abs/2403.00964v1
In Natural Language Generation (NLG), contemporary Large Language Models (LLMs) face several challenges, such as generating fluent yet inaccurate outputs and reliance on fluency-centric metrics. This often leads to neural networks exhibiting "halluci...
arxiv.org/abs/2602.06396v2
Semi-structured interviews are a common method in qualitative research. However, conducting high-quality interviews is cognitively demanding and requires strong interviewing skills. To lower this bar, we propose InterFlow, an AI-powered visual scaffo...
github.com/sukhpred/reactnd-project-would-you-rather
# Getting Started with Create React App This project was bootstrapped with [Create React App](https://github.com/facebook/create-react-app). ## Available Scripts In the project directory, you can run: ### `npm start` Runs the app in the development mode.\ Open…
github.com/adarshsingh10/my-movies-website
# Getting Started with Create React App This project was bootstrapped with [Create React App](https://github.com/facebook/create-react-app). ## Available Scripts In the project directory, you can run: ### `npm start` Runs the app in the development mode.\ Open…
apps.apple.com/us/app/mycricket-app/id626392754
Download myCricket App by Cricket Wireless, LLC on the App Store. See screenshots, ratings and reviews, user tips, and more apps like myCricket App.
arxiv.org/abs/2410.18287v1
Large language models (LLMs) are essential in natural language processing (NLP) but are costly in data collection, pre-training, fine-tuning, and inference. Task-specific small language models (SLMs) offer a cheaper alternative but lack robustness an...
developer.android.com/guide/topics/data
This document outlines the various options for saving app data on Android, categorizing them into app-specific, shared, preferences, and databases, while also explaining internal and external storage, permissions, and scoped storage.
arxiv.org/abs/1310.7141v1
Modern students encounter big, messy data sets long before setting foot in our classrooms. Many of our students need to develop skills in exploratory data analysis and multivariate analysis techniques for their jobs after college, but these topics ar...
github.com/paulcheng0830/Data-Analysis-Projects---Hong-Kong-Real-Estate-Market-Data-Analysis-2020
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arxiv.org/abs/2312.12464v2
We present a study on the integration of Large Language Models (LLMs) in tabular data classification, emphasizing an efficient framework. Building upon existing work done in TabLLM (arXiv:2210.10723), we introduce three novel serialization techniques...
arxiv.org/abs/2312.06731v6
Multimodal Large Language Models (MLLMs) demonstrate exceptional problem-solving capabilities, but few research studies aim to gauge the ability to generate visual instruction tuning data. This paper proposes to explore the potential of empowering ML...
arxiv.org/abs/2409.14281v2
The use of creative writing as training data for large language models (LLMs) is highly contentious and many writers have expressed outrage at the use of their work without consent or compensation. In this paper, we seek to understand how creative wr...
arxiv.org/abs/2312.14211v1
Open-source Large Language Models enable projects such as NASA SciX (i.e., NASA ADS) to think out of the box and try alternative approaches for information retrieval and data augmentation, while respecting data copyright and users' privacy. However,...
arxiv.org/abs/2507.07048v2
Large Multimodal Models (LMMs) are increasingly applied to meal images for nutrition analysis. However, existing work primarily evaluates proprietary models, such as GPT-4. This leaves the broad range of LLMs underexplored. Additionally, the influenc...
arxiv.org/abs/2501.14002v3
Mathematical reasoning remains a challenging area for large language models (LLMs), prompting the development of math-specific LLMs such as LLEMMA, DeepSeekMath, and Qwen2-Math, among others. These models typically follow a two-stage training paradig...
