Kevin Chen (chenwxOggai)

chenwxOggai

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Company:Fudan University, Shanghai

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Kevin Chen's starred repositories

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ReachQA

Code & Dataset for Paper: "Distill Visual Chart Reasoning Ability from LLMs to MLLMs"

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Awesome-LLM-Strawberry

A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 and reasoning techniques.

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AgentGym

Code and implementations for the paper "AgentGym: Evolving Large Language Model-based Agents across Diverse Environments" by Zhiheng Xi et al.

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LLM-and-Multimodal-Paper-List

A paper list about large language models and multimodal models (Diffusion, VLM). From foundations to applications. It is only used to record papers for my personal needs.

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LLM-Reverse-Curriculum-RL

Implementation of the ICML 2024 paper "Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning" presented by Zhiheng Xi et al.

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Awesome-LLM-Survey

An Awesome Collection for LLM Survey

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stanford_alpaca

Code and documentation to train Stanford's Alpaca models, and generate the data.

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chain-of-thought-hub

Benchmarking large language models' complex reasoning ability with chain-of-thought prompting

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FireAct

FireAct: Toward Language Agent Fine-tuning

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LLM-Agent-Paper-List

The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.

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Contrastive-Learning-NLP-Papers

Paper List for Contrastive Learning for Natural Language Processing

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Prompt-Engineering-Guide

🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

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LLMSurvey

The official GitHub page for the survey paper "A Survey of Large Language Models".

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955.WLB

955 不加班的公司名单 - 工作 955,work–life balance (工作与生活的平衡)

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manim

A community-maintained Python framework for creating mathematical animations.

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coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

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