Zihan Liu
2 indexed papers
Recent (6 mo)
2With code
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226
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Multiagent×1AI×1Crypto×1NLP×1Distributed×1ML×1
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2026
A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations
This survey provides a comprehensive, structured taxonomy of split learning techniques for fine-tuning Large Language Models (LLMs), covering model optimization, system efficiency, and privacy preservation.
Dynamic Trust-Aware Sparse Communication Topology for LLM-Based Multi-Agent Consensus
The paper proposes DySCo, a dynamic trust-aware sparse consensus mechanism, to efficiently manage communication in multi-agent LLM systems by selectively connecting agents based on real-time value, thus reducing overhead while maintaining critical cross-validation.
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Papers
cs.MAcs.AIRecentJun 1, 2026
Dynamic Trust-Aware Sparse Communication Topology for LLM-Based Multi-Agent Consensus
The paper proposes DySCo, a dynamic trust-aware sparse consensus mechanism, to efficiently manage communication in multi-agent LLM systems by selectively connecting agents based on real-time value, th…
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cs.CRcs.CLcs.DCRecentApr 27, 2026