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Seungone Kim (김승원)

Info about me...

Hello! I am an incoming Ph.D. student at Carnegie Mellon University and a M.S. Student at KAIST, advised by Minjoon Seo.

My primary research focus lies establishing a science of language model behaviors.
Concretely, my research interests include: (i) developing LLM evaluation frameworks that systematically identify what specific capabilities language models lack and (ii) improving language models with (human) feedback.

Reach out to me via email ([email protected]) if you have any questions, or would like to collaborate with me!

Seungone Kim's Projects

t-zero icon t-zero

Reproduce results and replicate training fo T0 (Multitask Prompted Training Enables Zero-Shot Task Generalization)

tk-instruct icon tk-instruct

Tk-Instruct is a Transformer model that is tuned to solve many NLP tasks by following instructions.

transformer_implementation icon transformer_implementation

'Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information processing systems. 2017.' (implementation from scratch with Pytorch)

transformers icon transformers

🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

trl icon trl

Train transformer language models with reinforcement learning.

trlx icon trlx

A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)

ver1.0 icon ver1.0

The first version of the Nuhnadulee Model (Vanilla Base Code)

web-llm icon web-llm

Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support.

ybigta_spring2021 icon ybigta_spring2021

This repository includes projects done in YBIGTA 2021 spring session(연세대학교 빅데이터 학회).

yonsei-nlp-study-season1 icon yonsei-nlp-study-season1

This repository contains presentation materials, links to presentation videos, and a summary of all the papers we have studied in Yonsei NLP Study Season1(2021.07.07~2021.08.25). Our main topic was Pretraining methods of Language Models, and other approaches to build up a better NLP Model. We have covered 37 papers in total!

yonsei-nlp-study-season2 icon yonsei-nlp-study-season2

This repository contains presentation materials, links to presentation videos, and a summary of all the papers we have studied in Yonsei NLP Study Season2(2021.09.08~2021.11.17). Our Main Topic was Question Answering and the various techniques needed to solve QA. We have covered 55 papers in total!

yonsei-nlp-study-season3 icon yonsei-nlp-study-season3

This repository contains presentation materials, links to presentation videos, and a summary of all the papers we have studied in Yonsei NLP Study Season3(2022.01.01~2022.03.01). Our Main Topic was Question Answering and Knowledge Distillation. We have covered 23 papers in total!

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