COCORELI: Enforcing Execution Preconditions for Reliable Collaborative Instruction Following

Researchers from multiple institutions, including Swarnadeep Bhar and Nicholas Asher, introduced COCORELI, a modular architecture that enforces missing information as a precondition for action, blocking execution until details are resolved through targeted clarification. In evaluations, COCORELI eliminated hallucinated actions by structurally coupling detection and prevention, while chain-of-thought, prompt-chaining, and ReAct-style reasoning still executed under incomplete specifications despite high detection rates. The system also generalized to API workflow tasks on ToolBench, demonstrating that reliable collaborative execution requires architectural enforcement, not just model capability.

COCORELI: Enforcing Execution Preconditions for Reliable Collaborative Instruction Following https://aclanthology.org/2026.sigdial-1.36.pdf Swarnadeep Bhar /people/swarnadeep-bhar/ , Omar Naim /people/omar-naim/ , Eleni Metheniti /people/eleni-metheniti/unverified/ , Loïc Cabannes /people/loic-cabannes/unverified/ , Bastien Navarri /people/bastien-navarri/unverified/ , Morteza Kamaladdini Ezzabady /people/morteza-kamaladdini-ezzabady/unverified/ , Nicholas Asher /people/nicholas-asher/unverified/ 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 to execution even after recognizing underspecification, leading to incorrect or unsafe actions. We identify this failure as arising from a lack of coupling between detection and execution, and propose that reliable behavior requires enforcing missing information as a precondition for action. We instantiate this principle in Cocoreli, a modular architecture that represents task structure, tracks missing information, and blocks execution until required details are resolved through targeted clarification. In Cocoreli, detection and prevention are structurally coupled: detecting a missing parameter simultaneously blocks execution. We evaluate Cocoreli in a controlled construction environment isolating underspecification and sequential execution. Cocoreli makes execution reliable by imposing explicit task structure: instructions are represented as parameterized executable objects and execution under unresolved specifications is blocked by construction, eliminating hallucinated actions. In contrast, chain-of-thought, prompt-chaining, and ReAct-style reasoning may still execute under incomplete specifications despite high detection rates. The same representation supports abstraction and reuse, and generalizes to API workflow tasks on ToolBench. These results show that reliable collaborative execution under underspecified instructions requires architectural enforcement, not just model capability.- Anthology ID: - 2026.sigdial-1.36 - Volume: Proceedings of the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue /volumes/2026.sigdial-1/ - Month: - August - Year: - 2026 - Address: - Atlanta, Georgia, USA - Editors: Jinho D. Choi /people/jinho-d-choi/ , Yun-Nung Chen /people/yun-nung-chen/ , Kotaro Funakoshi /people/kotaro-funakoshi/ , Ali Emami /people/ali-emami/ - Venue: SIGDIAL /venues/sigdial/ - SIG: SIGDIAL /sigs/sigdial/ - Publisher: - Association for Computational Linguistics - Note: - Pages: - 516–535 - Language: - URL: https://aclanthology.org/2026.sigdial-1.36/ https://aclanthology.org/2026.sigdial-1.36/ - DOI: - Cite ACL : - Swarnadeep Bhar, Omar Naim, Eleni Metheniti, Loïc Cabannes, Bastien Navarri, Morteza Kamaladdini Ezzabady, and Nicholas Asher. 2026. COCORELI: Enforcing Execution Preconditions for Reliable Collaborative Instruction Following https://aclanthology.org/2026.sigdial-1.36/ . In Proceedings of the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue , pages 516–535, Atlanta, Georgia, USA. Association for Computational Linguistics. - Cite Informal : COCORELI: Enforcing Execution Preconditions for Reliable Collaborative Instruction Following https://aclanthology.org/2026.sigdial-1.36/ Bhar et al., SIGDIAL 2026 - PDF: https://aclanthology.org/2026.sigdial-1.36.pdf https://aclanthology.org/2026.sigdial-1.36.pdf