Papers with constraint satisfaction rate

2 papers
Constrained Policy Optimization for Controlled Self-Learning in Conversational AI Systems (2023.acl-industry)

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Challenge: Recent self-learning methods based on user satisfaction metrics and contextual bandits have shown promising results to enable consistent improvements in conversational AI systems.
Approach: They propose a meta-gradient learning approach that adjusts constraint violation penalty terms adaptively through a user-defined meta objective that encourages balanced constraint satisfaction across domains.
Outcome: The proposed framework supports fine-grained exploration targets for individual domains via user-defined constraints.
Aligning to Constraints for Data-Efficient Language Model Customization (2025.findings-naacl)

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Challenge: General-purpose language models (LMs) are aligned to diverse user intents, but fall short when it comes to specific applications.
Approach: They propose a framework that uses constraints to automatically produce supervision signals for user alignment with constraints.
Outcome: The proposed framework can produce supervision signals for user alignment with constraints.

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