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

https://github.com/bigscience-workshop/promptsource

Finetuned Language Models Are Zero-Shot Learners

https://github.com/codelion/optillm/blob/main/optillm/mcts.py

Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

https://github.com/codelion/optillm/blob/main/optillm/self_consistency.py

Self-Consistency Improves Chain of Thought Reasoning in Language Models

https://github.com/declare-lab/puzzle-reasoning

The Jumping Reasoning Curve? Tracking the Evolution of Reasoning Performance in GPT-[n] and o-[n] Models on Multimodal Puzzles

https://github.com/elijahcn/TextCNN-AdversarialTraining

FreeLB: Enhanced Adversarial Training for Natural Language Understanding

https://github.com/fchollet/arc-agi

On the Measure of Intelligence

https://github.com/gair-nlp/prox

DataDecide: How to Predict Best Pretraining Data with Small Experiments

https://github.com/hari-sikchi/loop

Learning Off-Policy with Online Planning

https://github.com/hiyouga/llama-efficient-tuning

Finetuned Language Models Are Zero-Shot Learners

https://github.com/hojjat-mokhtarabadi/promptsource

Finetuned Language Models Are Zero-Shot Learners

https://github.com/hughbzhang/o1_inference_scaling_laws

Self-Consistency Improves Chain of Thought Reasoning in Language Models

https://github.com/ilialarchenko/abstract_reasoning

On the Measure of Intelligence

https://github.com/khalil-research/1d-arc

LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations

https://github.com/lastmile-ai/aiconfig/tree/main/cookbooks/Multi-LLM-Consistency

Self-Consistency Improves Chain of Thought Reasoning in Language Models

https://github.com/le-gris/h-arc

H-ARC: A Robust Estimate of Human Performance on the Abstraction and Reasoning Corpus Benchmark

https://github.com/meetyou-ai-lab/can-mc-evaluate-llms

Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

https://github.com/memory-overflow/standard-ellipse-detection

Arc-support Line Segments Revisited: An Efficient and High-quality Ellipse Detection

https://github.com/minhdng/market_microstructure

Universal scaling and nonlinearity of aggregate price impact in financial markets

https://github.com/openbiolink/promptsource

Finetuned Language Models Are Zero-Shot Learners

https://github.com/qxiaofan/awesome-High-quality-ellipse-detection

Arc-support Line Segments Revisited: An Efficient and High-quality Ellipse Detection

https://github.com/rasoolims/YaraParser

Yara Parser: A Fast and Accurate Dependency Parser

https://github.com/siqims/ARC-Challenge

Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question Answering

https://github.com/tanmay-delhikar/world-settlement-footprint

Outlining where humans live -- The World Settlement Footprint 2015

https://github.com/ukplab/arxiv2025-inherent-limits-plms

Finetuned Language Models Are Zero-Shot Learners

https://github.com/wujunjie1998/ref-long

Understanding LLMs' Fluid Intelligence Deficiency: An Analysis of the ARC Task

https://github.com/xuefuzhao/openmoe

ST-MoE: Designing Stable and Transferable Sparse Expert Models

https://github.com/yikangshen/megablocks

ST-MoE: Designing Stable and Transferable Sparse Expert Models

https://github.com/yzhangcs/parser

Efficient Second-Order TreeCRF for Neural Dependency Parsing

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