Papers with clipping mechanism
Accelerating Learned Sparse Indexes Via Term Impact Decomposition (2022.findings-emnlp)
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| Challenge: | Novel inverted index-based learned sparse ranking models provide more effective, but less efficient, retrieval performance compared to traditional ranking models. |
| Approach: | They propose a technique that allows for automatic pruning of ranking models by storing metadata about index term importance scores. |
| Outcome: | The proposed technique accelerates top-k retrieval by 9.6X without loss in effectiveness. |
CE-GPPO: Coordinating Entropy via Gradient-Preserving Clipping Policy Optimization in Reinforcement Learning (2026.acl-long)
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| Challenge: | Existing methods for proximal policy optimization discard valuable gradient signals from low-probability tokens due to the clipping mechanism. |
| Approach: | They propose an algorithm that reintroduces gradients from clipped tokens in native PPO in a gentle and bounded manner. |
| Outcome: | The proposed algorithm outperforms strong baselines on reasoning benchmarks on different model scales. |