MemEvolve jointly evolves agent experiential knowledge and memory architectures via a modular codebase, delivering up to 17% gains on agent benchmarks with cross-task and cross-model generalization.
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Complete cyclic subtask graphs offer a lens to measure when multi-agent revisitation aids recovery and exploration versus when it increases costs or is dominated by other bottlenecks in LLM agent workflows.
OxyGent supplies a modular framework for multi-agent systems via the Oxy abstraction for composition and monitoring and the OxyBank engine for continuous automated evolution.
citing papers explorer
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MemEvolve: Meta-Evolution of Agent Memory Systems
MemEvolve jointly evolves agent experiential knowledge and memory architectures via a modular codebase, delivering up to 17% gains on agent benchmarks with cross-task and cross-model generalization.
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Complete Cyclic Subtask Graphs for Tool-Using LLM Agents: Flexibility, Cost, and Bottlenecks in Multi-Agent Workflows
Complete cyclic subtask graphs offer a lens to measure when multi-agent revisitation aids recovery and exploration versus when it increases costs or is dominated by other bottlenecks in LLM agent workflows.
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OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction
OxyGent supplies a modular framework for multi-agent systems via the Oxy abstraction for composition and monitoring and the OxyBank engine for continuous automated evolution.