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Cocreli architecture enforces preconditions for reliable instruction following

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced Cocoreli, a novel architecture designed to enhance the reliability of autonomous agents executing human instructions. Cocoreli addresses the issue of agents proceeding with actions despite incomplete or underspecified instructions by structurally coupling detection of missing information with execution blocking. This ensures that agents only execute tasks once all necessary preconditions are met, preventing incorrect or unsafe actions. The system has demonstrated effectiveness in controlled environments and on API workflow tasks, outperforming existing reasoning methods in preventing execution under unresolved specifications. AI

IMPACT This architecture could improve the safety and reliability of AI agents in complex task execution.

RANK_REASON This is a research paper detailing a new architecture for autonomous agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Cocreli architecture enforces preconditions for reliable instruction following

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This is a research paper detailing a new architecture for autonomous agents. [lever_c_demoted from research: ic=1 ai=1.0]
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119 days old
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Swarnadeep Bhar, Omar Naim, Eleni Metheniti, Bastien Navarri, Lo\"ic Cabannes, Morteza Ezzabady, Nicholas Asher ·

    COCORELI: Enforcing Execution Preconditions for Reliable Collaborative Instruction Following

    arXiv:2509.04470v2 Announce Type: replace Abstract: Autonomous agents executing human instructions must operate reliably even when instructions are incomplete. While recent approaches improve detection of missing information, detection alone is insufficient: agents often proceed …

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