DDCOT

Prompting library

This implementation provides tools and methods for multimodal reasoning in language models through prompting.

[NeurIPS 2023]DDCoT: Duty-Distinct Chain-of-Thought Prompting for Multimodal Reasoning in Language Models

GitHub

35 stars
2 watching
1 forks
Language: Python
last commit: 10 months ago

Related projects:

Repository Description Stars
dvlab-research/prompt-highlighter An interactive control system for text generation in multi-modal language models 135
ju-bezdek/langchain-decorators Provides syntactic sugar for writing custom LangChain prompts and chains, making it easier to write more pythonic code. 228
ailab-cvc/seed An implementation of a multimodal language model with capabilities for comprehension and generation 585
ailab-cvc/seed-bench A benchmark for evaluating large language models' ability to process multimodal input 322
davebshow/gremlinclient Client library for interacting with the Gremlin Server protocol in Python 28
mwydmuch/napkinxc A fast and simple library for multi-class and multi-label classification 65
ncwilson78/system-prompt-library A comprehensive collection of customizable prompts for Generative Pre-trained Transformers (GPTs) designed specifically for educational use. 77
mshukor/evalign-icl Evaluating and improving large multimodal models through in-context learning 21
dmulyalin/ttp A template-based text parsing library 353
dcdmllm/cheetah A large language model designed to understand and generate instructions with accompanying visual content 360
uw-madison-lee-lab/cobsat Provides a benchmarking framework and dataset for evaluating the performance of large language models in text-to-image tasks 30
maciej-gol/tenant-schemas-celery Enables collaboration between Celery tasks and multi-tenancy in Django applications. 183
agkozak/polyglot A dynamic shell prompt that displays various information in ASCII format, including username, session type, Git branch and status, exit status, and virtual environment information. 182
multimodal-art-projection/omnibench Evaluates and benchmarks multimodal language models' ability to process visual, acoustic, and textual inputs simultaneously. 15
zjunlp/mol-instructions A dataset and tools package designed to support the training and evaluation of large language models for molecular biology tasks 255