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Logic Grid Puzzle

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/Hyun-Ryu/clover

공식 코드

Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning

https://github.com/mikewangwzhl/solo-performance-prompting

공식 코드

Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration

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/chrisociepa/allamo

PaLM: Scaling Language Modeling with Pathways

https://github.com/conceptofmind/PaLM-flax

PaLM: Scaling Language Modeling with Pathways

https://github.com/foundation-model-stack/fms-fsdp

PaLM: Scaling Language Modeling with Pathways

https://github.com/google/paxml

PaLM: Scaling Language Modeling with Pathways

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

Training Compute-Optimal Large Language Models

https://github.com/lucidrains/CoCa-pytorch

PaLM: Scaling Language Modeling with Pathways

https://github.com/lucidrains/PaLM-jax

PaLM: Scaling Language Modeling with Pathways

https://github.com/lucidrains/PaLM-pytorch

PaLM: Scaling Language Modeling with Pathways

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

Training Compute-Optimal Large Language Models

https://github.com/profsynapse/synapse_cor

Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration

https://github.com/rvlopes/gloria

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

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