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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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코드

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

https://github.com/cleverhans-lab/verifiable-unlearning

공식 코드

Verifiable and Provably Secure Machine Unlearning

https://github.com/mammadmaheri7/TeleSparseRepo

공식 코드

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks

https://github.com/allenai/dolma

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

https://github.com/bramiozo/PubScience

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

https://github.com/karpathy/llama2.c

Training Compute-Optimal Large Language Models

https://github.com/lyronctk/zator

Scaling up Trustless DNN Inference with Zero-Knowledge Proofs

https://github.com/nkluge-correa/teenytinyllama

Training Compute-Optimal Large Language Models

https://github.com/open-finance-lab/finlora

BloombergGPT: A Large Language Model for Finance

https://github.com/rvlopes/gloria

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

https://github.com/yangletliu/finlora

BloombergGPT: A Large Language Model for Finance

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