Papers with Inference-time alignment methods

1 papers
From Outcomes to Processes: Guiding PRM Learning from ORM for Inference-Time Alignment (2025.acl-long)

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Challenge: Existing approaches to align large language models with human preferences suffer from inconsistent scoring and suboptimal alignment.
Approach: They propose a dual-consistency framework that aligns partial sequences with human preferences.
Outcome: The proposed framework significantly reduces granularity discrepancies and improves GPT-4 evaluation scores.

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