zjunlp / MachineSoM

[ACL 2024] Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View

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Nice Work

mczhuge opened this issue · comments

This is promising work. The AI/ML community will recognize the value of thinking about AI in a Society of Mind way.

Keep going!

Dear Mingchen,

We would like to extend our heartfelt gratitude for your kind words and recognition of our work. It's truly motivating to receive such positive feedback, especially from esteemed colleagues like yourself.

We're excited to share that our project is progressing well and is currently ongoing. We are in the process of updating our manuscript on arXiv with more comprehensive experiments and in-depth analyses. The upcoming update will be substantial, featuring over 60 pages of content (with 8 dedicated to the main text), enriched with 67 figures and 37 tables. We believe this extensive update will offer valuable insights into our research, and we warmly invite you to follow our progress.

By the way, we must mention that your work, particularly on MetaGPT, has been a significant source of inspiration for us. The innovative approach to multi-agent collaboration in MetaGPT stands out as exemplary work in the field, and we've gleaned a lot of insights from it.

Once again, thank you for your support and recognition. We look forward to any future opportunities for collaboration or discussion that might arise from our shared interests in advancing multi-agent collaboration research.

Best Regards,
All Authors.

Thank you for your kind words, which also motivate me to improve.

Wow, 67 figures and 37 tables! That would be lovely!

Looking forward to your updates and new paper, and good luck with everything! :)

commented

Thank you for your kind words, which also motivate me to improve.

Wow, 67 figures and 37 tables! That would be lovely!

Looking forward to your updates and new paper, and good luck with everything! :)

hi, the paper is available here: https://arxiv.org/abs/2310.02124

We also provide a project website: https://www.zjukg.org/project/MachineSoM/

Best,

All Authors.