Scaling Unverifiable Rewards: A Case Study on Visual Insights (2026.findings-acl)
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| Challenge: | Existing methods to scale complex, open-ended tasks with unverifiable rewards are not scalable to multi-stage pipelines. |
| Approach: | They propose a process-based refinement framework that scales inference across stages of a multi-agent pipeline, instead of refining a single output over time. |
| Outcome: | The proposed framework scales inference across stages of a multi-agent pipeline, instead of refining a single output over time as in prior work. |
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