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This project is a multimodal large language model reasoning framework designed to train and evaluate models in performing chain-of-thought reasoning across text and image data. It provides a reasoning engine and training system that enable vision-language models to generate step-by-step logical rationales and final answers for complex queries. The framework utilizes a two-stage training pipeline that decouples the generation of logical justifications from final answer inference. It transforms visual data into descriptive text through image captioning and uses vision-transformer feature extrac
[Website](http://craftjarvis-jarvis1.github.io/) [Paper](https://arxiv.org/abs/2311.05997) [Twitter](https://twitter.com/jeasinema/status/1723900032653643796)
This is an LLM agent framework and symbolic learning system designed for building self-evolving autonomous agents. It functions as a computational graph orchestrator that organizes agent interactions and tool sequences as a trainable graph of nodes. The framework focuses on data-centric agent optimization, allowing agent pipelines and prompts to be upgraded through data-driven training rather than manual engineering. It utilizes a symbolic learning process that applies language-based loss and textual reflections to refine the operational logic and symbolic components of an agent. The system
We instantiate Pangu on knowledge base question answering (KBQA), which is representative testbed for grounded language understanding with a highly complex and heterogeneous environment.
The main features of dki-lab/pangu are: Reasoning And Planning, Database Interfaces.
Open-source alternatives to dki-lab/pangu include: amazon-science/mm-cot — This project is a multimodal large language model reasoning framework designed to train and evaluate models in… ber666/rap. craftjarvis/jarvis-1 — [[Website]](http://craftjarvis-jarvis1.github.io/) [[Paper]](https://arxiv.org/abs/2311.05997)… craftjarvis/mc-planner. cranial-xix/llm-pddl — This repo contains the source code for making plans based on problems decribed by natural language. aiwaves-cn/agents — This is an LLM agent framework and symbolic learning system designed for building self-evolving autonomous agents. It…