Papers with Code 아카이브

Multi-task Language Understanding

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 5
보존된 평가 기록: 79

The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more. https://arxiv.org/pdf/2009.03300.pdf

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/zfj1998/CodeBert-Code2Text

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/zhaoolee/garss

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

https://github.com/zhuzilin/ring-flash-attention

The Llama 3 Herd of Models

https://github.com/zihanzhaosjtu/librisqa

LLaMA: Open and Efficient Foundation Language Models

https://github.com/ziye2chen/LLMs-for-Mathematical-Analysis

The Llama 3 Herd of Models

https://github.com/znhy1024/protoco

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/zphang/lm_evaluation_harness

Language Models are Few-Shot Learners

https://github.com/zurichnlp/contradecode

Llama 2: Open Foundation and Fine-Tuned Chat Models

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.