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Introducing MoCo, the first open-source Python package for model collaboration, where multiple LLMs collaborate, compose, and complement each other.
Code: github.com/BunsenFeng/mod…
Paper: arxiv.org/abs/2601.21257
Shangbin Feng
1,238 posts
- Thrilled (and frightened) that I recently won: - IBM PhD Fellowship - Baidu PhD Fellowship - Jane Street Fellowship Super grateful for the support! Hopefully I can do something that deserves these recognitions.
- 👀 How to find a better adapted model? ✨ Let the models find it for you! 👉🏻 Introducing Model Swarms, multiple LLM experts collaboratively search for new adapted models in the weight space and discover their new capabilities. 📄 Paper: arxiv.org/abs/2410.11163
- Do LLMs have inherent political leanings? How do their political biases impact downstream tasks? We answer these questions in our #ACL2023 paper: "From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models"
- LLMs are adopted in tasks and contexts with implicit graph structures, but ... Are LMs graph reasoners? Can LLMs perform graph-based reasoning in natural language? Introducing NLGraph, a comprehensive testbed of graph-based reasoning designed for LLMs arxiv.org/abs/2305.10037
- Ever felt hopeless when LLMs make factual mistakes? Always waiting for big companies to release LLMs with improved knowledge abilities? Introducing CooK, a community-driven initiative to empower black-box LLMs with modular and collaborative knowledge arxiv.org/abs/2305.09955
- Don't hallucinate, abstain! #ACL2024 "Hey ChatGPT, is your answer true?" Sadly LLMs can't reliably self-eval/self-correct :( Introducing teaching LLMs to abstain via multi-LLM collaboration! A thread 🧵
- First paper to make 100 and also my first ever paper, where it all started 🥥
- One LLM is not enough. We need multi-LLM collaboration for collaborative development and compositional intelligence. Our thoughts: arxiv.org/abs/2502.04506
- 👀 How to find more difficult/novel/salient evaluation data? ✨ Let the data generators find it for you! Introducing Data Swarms, multiple data generator LMs collaboratively search in the weight space to optimize quantitative desiderata of evaluation.
- 👀 How to effectively leverage the expertise of diverse models? ✨ Optimize graphs of LLMs with swarm intelligence! 👉🏻 Introducing Heterogeneous Swarms, jointly optimizing the roles and weights of multi-LLM systems for collaborative gains! 📄 Paper: arxiv.org/abs/2502.04510
- ACL Accepts: LLMs+ abstain arxiv.org/abs/2402.00367 detect and design social bots arxiv.org/abs/2402.00371 geometric knowledge reasoning arxiv.org/abs/2310.01290 simulate reactions to detect misinfo arxiv.org/abs/2402.10426 robustness of AI text detection arxiv.org/abs/2402.11638
