CoCoA Framework:The top part is CoCoA-zero, a multi-agent collaboration framework. It integrates internal and external knowledge in a collaborative manner by first performing knowledge induction and then making decisions. The bottom part is the training strategy, which is based on CoCoA-zero and combines the trajectories of different agents into long chains to train and enhance the integration ability of the LLM.
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The main dependencies are torch 2.5.1, vllm 0.7.3, DeepSpeed, trl, peft, faiss/faiss-gpu.
conda create -n CoCoA python=3.9.18
conda activate CoCoA
pip install -r requirements.txtDownload Corpus & Index
Retrieval is performed on the set of Wikipeda passages used in DPR. Download passages:
wget https://dl.fbaipublicfiles.com/dpr/wikipedia_split/psgs_w100.tsv.gzDownload passage embeddings pre-computed with Contriever or Contriever-msmarco:
wget https://dl.fbaipublicfiles.com/contriever/embeddings/contriever/wikipedia_embeddings.tar
wget https://dl.fbaipublicfiles.com/contriever/embeddings/contriever-msmarco/wikipedia_embeddings.tarRetrieve top-k passages:
cd ./retrieval
python retrieval_engine.py # Remember to configure your parametersTraining
cd scripts
bash xxx.sh # You can view the scripts provided in the scripts directoryDownload Evaluation Data:
Details will be completed soon
@article{jiang2025collaborative,
title={Collaborative Chain-of-Agents for Parametric-Retrieved Knowledge Synergy},
author={Jiang, Yi and Zhao, Sendong and Li, Jianbo and Wang, Haochun and Zhang, Lizhe and Liu, Yan and Qin, Bing},
journal={arXiv preprint arXiv:2508.01696},
year={2025}
}Thanks for your interest in our work!