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In-Context Learning

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

https://github.com/zirui-HIT/Fused

공식 코드

Improving Demonstration Diversity by Human-Free Fusing for Text-to-SQL

https://github.com/zirui-HIT/ICTL

공식 코드

In-Context Transfer Learning: Demonstration Synthesis by Transferring Similar Tasks

https://github.com/zju-daily/aistorian

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AIstorian lets AI be a historian: A KG-powered multi-agent system for accurate biography generation

https://github.com/zjukg/kopa

공식 코드

Making Large Language Models Perform Better in Knowledge Graph Completion

https://github.com/zjukg/ontotune

공식 코드

OntoTune: Ontology-Driven Self-training for Aligning Large Language Models

https://github.com/zjunlp/DeepKE/tree/main/example/llm

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How to Unleash the Power of Large Language Models for Few-shot Relation Extraction?

https://github.com/zjunlp/deepke

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How to Unleash the Power of Large Language Models for Few-shot Relation Extraction?

https://github.com/zjunlp/knowledgecircuits

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Knowledge Circuits in Pretrained Transformers

https://github.com/zkx06111/llm_priming

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Large Language Models Are Partially Primed in Pronoun Interpretation

https://github.com/zlkong/awesome-token-compression-reduction

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Token Reduction Should Go Beyond Efficiency in Generative Models -- From Vision, Language to Multimodality

https://github.com/zlkqz/auto_eval

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TALEC: Teach Your LLM to Evaluate in Specific Domain with In-house Criteria by Criteria Division and Zero-shot Plus Few-shot

https://github.com/znhy1024/protoco

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Prompt to be Consistent is Better than Self-Consistent? Few-Shot and Zero-Shot Fact Verification with Pre-trained Language Models

https://github.com/zodiark-ch/emergence-of-llms

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Quantifying Semantic Emergence in Language Models

https://github.com/zodiark-ch/language-skill-of-llms

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Unveiling Language Skills via Path-Level Circuit Discovery

https://github.com/zyxnlp/icl-interpretation-analysis-resources

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The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysis

https://github.com/zzhao71/ripplecot

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RIPPLECOT: Amplifying Ripple Effect of Knowledge Editing in Language Models via Chain-of-Thought In-Context Learning

https://github.com/zzz47zzz/codebase-for-incremental-learning-with-llm

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Can LLMs Learn New Concepts Incrementally without Forgetting?

https://github.com/zzz47zzz/pretrained-lm-for-incremental-learning

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Can LLMs Learn New Concepts Incrementally without Forgetting?

https://gitlab.com/folbaeni/multimodal-icl

공식 코드

What Makes Multimodal In-Context Learning Work?

https://huggingface.co/spaces/herilalaina/ifbo

공식 코드

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization

https://github.com/0417keito/JEN-1-COMPOSER-pytorch

JEN-1: Text-Guided Universal Music Generation with Omnidirectional Diffusion Models

https://github.com/0417keito/JEN-1-pytorch

JEN-1: Text-Guided Universal Music Generation with Omnidirectional Diffusion Models

https://github.com/2023-MindSpore-1/ms-code-14/tree/main/Pangu_alpha

PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation

https://github.com/2023-MindSpore-1/ms-code-162

PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation

https://github.com/2023-MindSpore-4/Code4/tree/main/FBPrompt-main

Enhancing In-Context Learning with Answer Feedback for Multi-Span Question Answering

https://github.com/2noise/chattts

Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers

https://github.com/BigBinnie/Benchmarking-LLM-based-Machine-Translation-on-Cultural-Awareness

Benchmarking Machine Translation with Cultural Awareness

https://github.com/EVOKE-LMM/EVOKE

In-Context Editing: Learning Knowledge from Self-Induced Distributions

https://github.com/FKIRSTE/emnlp2024-personalized-meeting-sum

Calibrating LLM-Based Evaluator

https://github.com/Ipsedo/TabPFN

TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second

https://github.com/JoegameZhou/mPanGu-Alpha-53

PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation

https://github.com/LautaroEst/efficient-reestimation

Unsupervised Calibration through Prior Adaptation for Text Classification using Large Language Models

https://github.com/MS-P3/code6/tree/main/parallel

Parallel Structures in Pre-training Data Yield In-Context Learning

https://github.com/NVlabs/Sana

SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

https://github.com/One-2-3-45/One-2-3-45

MIMIC-IT: Multi-Modal In-Context Instruction Tuning

https://github.com/RUCAIBox/LLMBox

Large Language Models Are Human-Level Prompt Engineers

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