Papers by Zhiliang wu
One Refiner to Unlock Them All: Inference-Time Reasoning Elicitation via Reinforcement Query Refinement (2026.acl-long)
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| Challenge: | Existing alignment methods for Large Language Models (LLMs) are expensive and lack the flexibility to fully activate their latent reasoning capabilities. |
| Approach: | They propose a modular framework that treats reasoning elicitation as an inference-time alignment task. |
| Outcome: | The proposed framework outperforms baselines by 2.1% on average across diverse architectures and benchmarks. |