Search Results for "human resource"
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Showing 10 open source projects for "human resource"
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LLM-Agent-Paper-List
The paper list of the 86-page SCIS cover paper
LLM-Agent-Paper-List is an open-source research repository that aggregates and organizes academic publications related to large language model–based agents. The project functions as a curated companion resource to a comprehensive survey paper examining the rise and potential of LLM-driven agent systems. Within the repository, research papers are categorized according to key aspects of agent architecture, including components such as reasoning systems, perception mechanisms, and action modules. The project also organizes literature into thematic sections that explore different application scenarios, including single-agent systems, collaborative multi-agent environments, and human-agent interaction. ... -
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The Alignment Handbook
Robust recipes to align language models with human and AI preferences
The Alignment Handbook is an open-source resource created to provide practical guidance for aligning large language models with human preferences and safety requirements. The project focuses on the post-training stage of model development, where models are refined after pre-training to behave more helpfully, safely, and reliably in real-world applications. It provides detailed training recipes that explain how to perform tasks such as supervised fine-tuning, preference modeling, and reinforcement learning from human feedback. ... -
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CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
...Our approach involves using inception prompting to guide chat agents toward task completion while maintaining consistency with human intentions. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of chat agents, providing a valuable resource for investigating conversational language models. -
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The LLM Evaluation guidebook
Sharing both practical insights and theoretical knowledge about LLM
...It discusses multiple evaluation strategies, ranging from automated benchmarks to human evaluation and LLM-based evaluation techniques. The material also highlights the strengths and weaknesses of different evaluation methods, helping practitioners understand when and how to apply them. By organizing evaluation knowledge into structured sections, the project helps engineers and researchers build more reliable and trustworthy AI systems. -
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LLM Course
Course to get into Large Language Models (LLMs)
LLM Course is a hands-on, notebook-driven path for learning how large language models work in practice, from data curation to training, fine-tuning, evaluating, and deploying. It emphasizes reproducible experiments: each step is demonstrated with runnable code, clear dependencies, and references to commonly used open-source models and libraries. Learners get exposure to multiple adaptation strategies—LoRA/QLoRA, instruction fine-tuning, and alignment techniques—so they can choose approaches... -
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NLP
Open source NLP guide with models, methods, and real use cases
NLP is an open source introductory resource for natural language processing, presented as a continuously updated book hosted on GitHub. It explains how machines process and understand human language, combining theory with practical examples. Its covers core NLP concepts such as text representation, feature extraction, and model evaluation, alongside hands-on implementations using tools like Word2Vec, TF-IDF, and FastText. -
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dots.ocr
Multilingual Document Layout Parsing in a Single Vision-Language Model
...Unlike traditional OCR pipelines that rely on multiple specialized components, dots.ocr integrates these processes end-to-end, reducing error propagation and improving consistency across tasks. The model is designed to recognize virtually any human script, making it highly effective for global and low-resource language scenarios. It achieves state-of-the-art performance on document parsing benchmarks while maintaining a relatively compact model size, demonstrating efficiency without sacrificing accuracy. Beyond standard OCR tasks, it extends its capabilities to parse complex visual elements such as charts, diagrams, and web interfaces, converting them into structured outputs like SVG code. -
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MoveNet
A CNN model that predicts human joints from RGB images of a person
The MoveNet model is an efficient, real-time human pose estimation system designed for detecting and tracking keypoints of human bodies. It utilizes deep learning to accurately locate 17 key points across the body, providing precise tracking even with fast movements. Optimized for mobile and embedded devices, MoveNet can be integrated into applications for fitness tracking, augmented reality, and interactive systems. -
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Safety-Prompts
Chinese safety prompts for evaluating and improving the safety of LLMs
...The project focuses primarily on safety testing scenarios relevant to Chinese language models, though the concepts can be applied to other languages and systems. The prompts are structured to test whether models generate outputs that align with human values and safety guidelines when faced with potentially harmful or sensitive requests. Researchers and developers use the dataset to benchmark how well models avoid unsafe responses and follow alignment constraints. The repository also serves as a training resource for improving model alignment by providing examples of prompts that require safe reasoning and appropriate refusal behavior. ... -
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OpenCE
Contrast Enhancement Techniques for low-light images
...It supports standard human pose estimation benchmarks such as COCO, with configurations optimized for accuracy and efficiency. As an open resource, OpenCE offers researchers and practitioners a strong baseline for pose estimation and a foundation for extending CPN-based methods.
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