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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/tongshuangwu/scattershot

공식 코드

ScatterShot: Interactive In-context Example Curation for Text Transformation

https://github.com/tonyzhou98/concept-spurious-correlation

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Explore Spurious Correlations at the Concept Level in Language Models for Text Classification

https://github.com/tqfang/event-temporal-knowledge-conflict

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Getting Sick After Seeing a Doctor? Diagnosing and Mitigating Knowledge Conflicts in Event Temporal Reasoning

https://github.com/travis-xu/TR-Feedback

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Enhancing Tool Retrieval with Iterative Feedback from Large Language Models

https://github.com/tri-ml/linear_open_lm

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Linearizing Large Language Models

https://github.com/trishullab/copra

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An In-Context Learning Agent for Formal Theorem-Proving

https://github.com/tsunehiko/ggdg

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Grammar-based Game Description Generation using Large Language Models

https://github.com/tung-nd/expt

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ExPT: Synthetic Pretraining for Few-Shot Experimental Design

https://github.com/txsun1997/black-box-tuning

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Black-Box Tuning for Language-Model-as-a-Service

https://github.com/ubecc/generalization-of-transformers

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Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study

https://github.com/ubiquitouslearning/slm_survey

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Small Language Models: Survey, Measurements, and Insights

https://github.com/uds-lsv/llmft

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Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation

https://github.com/uds-lsv/multilingual-icl-analysis

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The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis

https://github.com/uestc-gqj/tkre

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Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-training

https://github.com/ukplab/acl2024-ood-compuational-argumentation

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How to Handle Different Types of Out-of-Distribution Scenarios in Computational Argumentation? A Comprehensive and Fine-Grained Field Study

https://github.com/ukplab/arxiv2024-conditional-reasoning-llms

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Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs

https://github.com/ukplab/arxiv2025-icl-investigation

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Illusion or Algorithm? Investigating Memorization, Emergence, and Symbolic Processing in In-Context Learning

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

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The Inherent Limits of Pretrained LLMs: The Unexpected Convergence of Instruction Tuning and In-Context Learning Capabilities

https://github.com/ukplab/in-context-pvi

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Measuring Pointwise $\mathcal{V}$-Usable Information In-Context-ly

https://github.com/ukplab/naacl2024-prompt-sensitivity

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How are Prompts Different in Terms of Sensitivity?

https://github.com/ukplab/on-emergence

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Are Emergent Abilities in Large Language Models just In-Context Learning?

https://github.com/umass-ml4ed/prompt_distractor_generation_naacl

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Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models

https://github.com/umass-ml4ed/reticl

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RetICL: Sequential Retrieval of In-Context Examples with Reinforcement Learning

https://github.com/ur-whitelab/bo-icl

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Bayesian Optimization of Catalysis With In-Context Learning

https://github.com/ur-whitelab/bo-lift

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Bayesian Optimization of Catalysis With In-Context Learning

https://github.com/usc-isi-i2/isi-tkg-icl

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Temporal Knowledge Graph Forecasting Without Knowledge Using In-Context Learning

https://github.com/ut-austin-rpl/amago

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AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents

https://github.com/uw-bionlp/CACER

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CACER: Clinical Concept Annotations for Cancer Events and Relations

https://github.com/uw-bionlp/pedshac

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Extracting Social Determinants of Health from Pediatric Patient Notes Using Large Language Models: Novel Corpus and Methods

https://github.com/uw-madison-lee-lab/cobsat

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Can MLLMs Perform Text-to-Image In-Context Learning?

https://github.com/uw-madison-lee-lab/dual_operating_modes_of_icl

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Dual Operating Modes of In-Context Learning

https://github.com/uw-madison-lee-lab/icl-hcg

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In-Context Learning with Hypothesis-Class Guidance

https://github.com/v7labs/xmem_icl

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Flexible visual prompts for in-context learning in computer vision

https://github.com/vdblm/CausalPFN

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CausalPFN: Amortized Causal Effect Estimation via In-Context Learning

https://github.com/vim-bench/vim_tool

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Text as Images: Can Multimodal Large Language Models Follow Printed Instructions in Pixels?

https://github.com/virobo-15/mgcc

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Multi-modal Generation via Cross-Modal In-Context Learning

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