ReAct-based agents typically rely on a single LLM policy to propose actions, interact with the environment, and decide when a task is complete. This coupling makes action authorization and completion control difficult to enforce independently, allowing errors to propagate and unsupported completion claims to terminate...
Ajay Vohra, Tao Chen, Neeti Narayan et al.· 0 citations
The Third Workshop on Agentic and Generative AI for E-Commerce, co-located with the 20th ACM Conference on Recommender Systems (RecSys 2026), brings together researchers and practitioners to examine the rapidly evolving intersection of recommender systems, generative AI, and agentic AI in online retail. As AI systems e...
M. Mane, Neeti Narayan, Djordje Gligorijevic et al.· Proceedings of the 20th ACM...· 0 citations
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