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Guangchun Luo

2 accepted papers

2025

BDCKD: Unlocking the Power of Brownian Distance Covariance in Knowledge Distillation

ICASSP 2025accepted

Knowledge distillation has been proven to be an effective method for enhancing model performance, particularly in the domain of model compression. In this study, we propose a comprehensive approach that utilizes Brownian Distance Covariance (BDC) to measure the discrepancy between the logits produce…

Cited by 0SourceScholar
2025

DSAS: A Universal Plug-and-Play Framework for Attention Optimization in Multi-Document Question Answering

NeurIPS 2025poster

While large language models (LLMs) show considerable promise across various fields, they have notable limitations in handling multi-document question answering (Multi-doc QA) tasks. The first challenge is long-range dependency modeling, where LLMs struggle to focus on key information in long texts,…

Cited by 0SourceScholar