Papers by Xixi Wu
MoLoRAG: Bootstrapping Document Understanding via Multi-modal Logic-aware Retrieval (2025.emnlp-main)
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| Challenge: | Document Understanding is a foundational AI capability with broad applications . Large Vision-Language Models (LLMs) can't handle multi-page document comprehension . a logic-aware retrieval framework for multi-modal, multi- page document understanding is proposed . |
| Approach: | They propose a logic-aware retrieval framework for multi-modal, multi-page document understanding . MoLoRAG uses semantic and logical relevance to deliver more accurate retrieval . |
| Outcome: | The proposed framework improves on four DocQA datasets and demonstrates 9.68% accuracy improvement over existing methods. |
BrowseConf: Confidence-Guided Test-Time Scaling for Web Agents (2026.findings-acl)
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Litu Ou, Kuan Li, Huifeng Yin, Liwen Zhang, Zhongwang Zhang, Xixi Wu, Rui Ye, Zile Qiao, Yong Jiang, Pengjun Xie, Fei Huang, Jingren Zhou
| Challenge: | Existing work on confidence in LLMs is limited. |
| Approach: | They propose to use confidence scores to determine model answer quality and encourage model to try again until it reaches satisfactory confidence level. |
| Outcome: | The proposed methods significantly reduce token consumption while demonstrating competitive performance compared to baseline fixed budget methods. |