in-context-learning
There are 152 repositories under in-context-learning topic.
BradyFU/Awesome-Multimodal-Large-Language-Models
:sparkles::sparkles:Latest Advances on Multimodal Large Language Models
RUCAIBox/LLMSurvey
The official GitHub page for the survey paper "A Survey of Large Language Models".
mlfoundations/open_flamingo
An open-source framework for training large multimodal models.
atfortes/Awesome-LLM-Reasoning
From Chain-of-Thought prompting to OpenAI o1 and DeepSeek-R1 🍓
DSXiangLi/DecryptPrompt
总结Prompt&LLM论文，开源数据&模型，AIGC应用
zjunlp/LLMAgentPapers
Must-read Papers on LLM Agents.
baaivision/Painter
Painter & SegGPT Series: Vision Foundation Models from BAAI
lifeiteng/vall-e
PyTorch implementation of VALL-E(Zero-Shot Text-To-Speech), Reproduced Demo https://lifeiteng.github.io/valle/index.html
Timothyxxx/Chain-of-ThoughtsPapers
A trend starts from "Chain of Thought Prompting Elicits Reasoning in Large Language Models".
baaivision/Emu
Emu Series: Generative Multimodal Models from BAAI
EgoAlpha/prompt-in-context-learning
Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates. - Professor Yu Liu
bytedance/UNO
[ICCV 2025] 🔥🔥 UNO: A Universal Customization Method for Both Single and Multi-Subject Conditioning
quqxui/Awesome-LLM4IE-Papers
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
jxzhangjhu/Awesome-LLM-Uncertainty-Reliability-Robustness
Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models
Shark-NLP/OpenICL
OpenICL is an open-source framework to facilitate research, development, and prototyping of in-context learning.
jeffhj/LM-reasoning
This repository contains a collection of papers and resources on Reasoning in Large Language Models.
RenzeLou/awesome-instruction-learning
Papers and Datasets on Instruction Tuning and Following. ✨✨✨
zjunlp/EasyInstruct
[ACL 2024] An Easy-to-use Instruction Processing Framework for LLMs.
freshllms/freshqa
Data and code for FreshLLMs (https://arxiv.org/abs/2310.03214)
HenryHZY/Awesome-Multimodal-LLM
Research Trends in LLM-guided Multimodal Learning.
SynaLinks/synalinks
🧠🔗 From idea to production in just few lines: Graph-Based Programmable Neuro-Symbolic LM Framework - a production-first LM framework built with decade old Deep Learning best practices
archersama/awesome-recommend-system-pretraining-papers
Paper List for Recommend-system PreTrained Models
zhilizju/Awesome-instruction-tuning
A curated list of awesome instruction tuning datasets, models, papers and repositories.
xlang-ai/Binder
[ICLR 2023] Code for the paper "Binding Language Models in Symbolic Languages"
huangwl18/language-planner
Official Code for "Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents"
lzyhha/VisualCloze
[ICCV 2025] VisualCloze: A universal image generation framework that can support a wide range of in-domain tasks and generalize to unseen ones. (🔥 🔥 🔥 Merged into offical pipelines of diffusers.)
dunnolab/awesome-in-context-rl
Awesome In-Context RL: A curated list of In-Context Reinforcement Learning - - —
WHU-ZQH/ChatGPT-vs.-BERT
🎁[ChatGPT4NLU] A Comparative Study on ChatGPT and Fine-tuned BERT
MiZhenxing/ThinkDiff
ICML2025, I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models
ZhangYuanhan-AI/visual_prompt_retrieval
[NeurIPS2023] Official implementation and model release of the paper "What Makes Good Examples for Visual In-Context Learning?"
corl-team/rebased
Official implementation of the paper "Linear Transformers with Learnable Kernel Functions are Better In-Context Models"
luban-agi/Awesome-Tool-Learning
A curated list of papers and applications on tool learning.
IAAR-Shanghai/Grimoire
Grimoire is All You Need for Enhancing Large Language Models
xlang-ai/icl-selective-annotation
[ICLR 2023] Code for our paper "Selective Annotation Makes Language Models Better Few-Shot Learners"
p-lambda/incontext-learning
Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"
HKUNLP/icl-ceil
[ICML 2023] Code for our paper “Compositional Exemplars for In-context Learning”.