AI Research
Semantic Cooperative Games for Contribution Attribution in LLM-Based Multi-Agent Systems
Contribution attribution has become a central problem in LLM-based multi-agent systems, where final outputs are produced through multiple agents, message exchanges, and ordered workflow dependencies. Existing attribution methods often rely on counterfactual valuation, such as rem...
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ArXiv CS.AI
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ArXiv CS.AI
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This research tackles the crucial problem of attributing contributions within complex LLM multi-agent systems, moving beyond costly and inefficient counterfactual methods. By introducing Semantic Cooperative Games and the SLIC algorithm, it offers a more interpretable and computationally efficient way to understand agent impact.
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