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Awesome-LLM-Prompt-Optimization: a curated list of advanced prompt optimization and tuning methods in Large Language Models
[ICML 2024] One Prompt is Not Enough: Automated Construction of a Mixture-of-Expert Prompts - TurningPoint AI
LlamaIndex is the leading framework for building LLM-powered agents over your data.
Implementation of Toolformer, Language Models That Can Use Tools, by MetaAI
🦜🔗 Build context-aware reasoning applications
Open-source pre-training implementation of Google's LaMDA in PyTorch. Adding RLHF similar to ChatGPT.
HyDE: Precise Zero-Shot Dense Retrieval without Relevance Labels
A modular RL library to fine-tune language models to human preferences
An index of algorithms for offline reinforcement learning (offline-rl)
A curated list of awesome papers for Semantic Retrieval (TOIS Accepted: Semantic Models for the First-stage Retrieval: A Comprehensive Review).
[EMNLP 2023] Enabling Large Language Models to Generate Text with Citations. Paper: https://arxiv.org/abs/2305.14627
Companion repo for "Evaluating Verifiability in Generative Search Engines".
A repository for ACL 2022 paper "How do we answer complex questions: Discourse structure of long form answers"
WebGLM: An Efficient Web-enhanced Question Answering System (KDD 2023)
Forward-Looking Active REtrieval-augmented generation (FLARE)
ACL 2023 paper "A Critical Evaluation of Evaluations for Long-form Question Answering"
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
A dataset for training/evaluating Question Answering Retrieval models on ChatGPT responses with the possibility to training/evaluating on real human responses.
Examples and guides for using the OpenAI API
ColBERT: state-of-the-art neural search (SIGIR'20, TACL'21, NeurIPS'21, NAACL'22, CIKM'22, ACL'23, EMNLP'23)
[EMNLP 2022] This is the code repo for our EMNLP‘22 paper "COCO-DR: Combating Distribution Shifts in Zero-Shot Dense Retrieval with Contrastive and Distributionally Robust Learning".
MTEB: Massive Text Embedding Benchmark
A comprehensive list of Awesome Contrastive Learning Papers&Codes.Research include, but are not limited to: CV, NLP, Audio, Video, Multimodal, Graph, Language, etc.
Code for the paper "Simulating Bandit Learning from User Feedback for Extractive Question Answering".
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.