Papers by Pengju Ren
MIND: From Passive Mimicry to Active Reasoning through Capability-Aware Multi-Perspective CoT Distillation (2026.acl-long)
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Jin Cui, Jiaqi Guo, Jiepeng Zhou, Ruixuan Yang, Jiayi Lu, Jiajun Xu, Jiangcheng Song, Boran Zhao, Pengju Ren
| Challenge: | Existing approaches restrict students to following a single golden rationale and treat different reasoning paths independently, causing suboptimal performance. |
| Approach: | They propose a capability-adaptive framework that transitions distillation from passive mimicry to active cognitive construction and employ a feedback-driven inertia calibration mechanism to align supervision with the student’s current adaptability. |
| Outcome: | Experiments show that the proposed framework achieves state-of-the-art performance on both in-distribution and out-of distribution benchmarks. |
Jakiro: Boosting Speculative Decoding via Decoupled MoE (2026.acl-long)
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| Challenge: | Existing methods to accelerate large language model inference have a fundamental limitation: candidates at the same tree layer share identical feature representations, constraining diversity and diminishing overall effectiveness. |
| Approach: | They propose a decoupled mixture of experts (MoE) into a draft model to generate diverse tokens from distinct feature spaces. |
| Outcome: | The proposed approach achieves significant speedups over strong baselines, with notable improvements in non-greedy scenarios where token diversity is crucial. |