TACO: Tool-Augmented Credit Optimization for Agentic Tool Use
Tool-Augmented Credit Optimization (TACO) improves multimodal agent performance by distinguishing useful, redundant, or misleading code operations through dual advantage channels:…
Hugging Face · Daily Papers
·Mingkuan Feng, Jinyang Wu
·
·▲ 15 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Mingkuan Feng, Jinyang Wu, Hao Gu, Fangrui Lv, Ruihan Jin, Chuyuan Zhang
- 15 upvotes da comunidade
- Temas: agentic multimodal models, code-tool agents, GRPO, Differential Answer-Probe Reward, Outcome-Gated Advantage Routing, tool-contribution advantage
Resumo
Resumo original (em inglês), extraído do paper:
Tool-Augmented Credit Optimization (TACO) improves multimodal agent performance by distinguishing useful, redundant, or misleading code operations through dual advantage channels: Differential Answer-Probe Reward for individual tool contribution and Outcome-Gated Advantage Routing for final outcome distribution.Onde ler
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