H2O evicts non-heavy-hitter tokens from the KV cache using a dynamic submodular policy, retaining recent and frequent-co-occurrence tokens to reduce memory while preserving accuracy.
Gradientcoin: A peer-to-peer decentralized large language models
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DeRelayL is a proposed sustainable decentralized learning paradigm where permissionless participants relay-train and share models via designed incentives, backed by theoretical analysis and simulations.
Centralized-critic actor-critic training (CoLLM-CC) improves sample efficiency and stability over Monte-Carlo multi-agent RL for training decentralized LLM collaboration.
citing papers explorer
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H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
H2O evicts non-heavy-hitter tokens from the KV cache using a dynamic submodular policy, retaining recent and frequent-co-occurrence tokens to reduce memory while preserving accuracy.
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DeRelayL: Sustainable Decentralized Relay Learning
DeRelayL is a proposed sustainable decentralized learning paradigm where permissionless participants relay-train and share models via designed incentives, backed by theoretical analysis and simulations.
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Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic
Centralized-critic actor-critic training (CoLLM-CC) improves sample efficiency and stability over Monte-Carlo multi-agent RL for training decentralized LLM collaboration.