Papers by Ruizhi Chen
HiChunk: Evaluating and Enhancing Retrieval Augmented Generation with Hierarchical Chunking (2026.acl-long)
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| Challenge: | Existing evaluation benchmarks for document chunking are inadequate due to evidence sparsity . evaluators are unable to evaluate different chunking methods due to the evidence sparing . |
| Approach: | They propose a QA benchmark for document chunking and a hierarchical document structuring framework for it. |
| Outcome: | The proposed framework improves document chunking quality within reasonable time consumption. |
QiMeng-Attention: SOTA Attention Operator is generated by SOTA Attention Algorithm (2025.findings-acl)
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Qirui Zhou, Shaohui Peng, Weiqiang Xiong, Haixin Chen, Yuanbo Wen, Haochen Li, Ling Li, Qi Guo, Yongwei Zhao, Ke Gao, Ruizhi Chen, Yanjun Wu, Zhao Chen, Yunji Chen
| Challenge: | Existing LLMs cannot comprehend the complex data flow and computation process of the attention operator and utilize low-level primitive to exploit GPU performance. |
| Approach: | They propose an LLM-friendly Thinking Language (LLM-TL) that can decouple the generation of high-level optimization logic and low-level implementation on GPU and enhance LLMs’ understanding of attention operator. |
| Outcome: | The proposed method outshines existing LLMs on A100, RTX8000, and T4 GPUs, achieving a speed-up of up to 35.16. |