Search Results for author: Weihao Liu

Found 10 papers, 5 papers with code

ERA-CoT: Improving Chain-of-Thought through Entity Relationship Analysis

1 code implementation11 Mar 2024 Yanming Liu, Xinyue Peng, Tianyu Du, Jianwei Yin, Weihao Liu, Xuhong Zhang

Large language models (LLMs) have achieved commendable accomplishments in various natural language processing tasks.

Question Answering

RA-ISF: Learning to Answer and Understand from Retrieval Augmentation via Iterative Self-Feedback

1 code implementation11 Mar 2024 Yanming Liu, Xinyue Peng, Xuhong Zhang, Weihao Liu, Jianwei Yin, Jiannan Cao, Tianyu Du

Large language models (LLMs) demonstrate exceptional performance in numerous tasks but still heavily rely on knowledge stored in their parameters.

Retrieval

TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering

no code implementations23 Oct 2023 Fangyu Lei, Tongxu Luo, Pengqi Yang, Weihao Liu, Hanwen Liu, Jiahe Lei, Yiming Huang, Yifan Wei, Shizhu He, Jun Zhao, Kang Liu

Table-based question answering (TableQA) is an important task in natural language processing, which requires comprehending tables and employing various reasoning ways to answer the questions.

Question Answering

Modality Unifying Network for Visible-Infrared Person Re-Identification

no code implementations ICCV 2023 Hao Yu, Xu Cheng, Wei Peng, Weihao Liu, Guoying Zhao

Visible-infrared person re-identification (VI-ReID) is a challenging task due to large cross-modality discrepancies and intra-class variations.

Person Re-Identification

MMHQA-ICL: Multimodal In-context Learning for Hybrid Question Answering over Text, Tables and Images

no code implementations9 Sep 2023 Weihao Liu, Fangyu Lei, Tongxu Luo, Jiahe Lei, Shizhu He, Jun Zhao, Kang Liu

Most importantly, we propose a Type-specific In-context Learning Strategy for MMHQA, enabling LLMs to leverage their powerful performance in this task.

In-Context Learning Question Answering +1

Advancing Topic Segmentation and Outline Generation in Chinese Texts: The Paragraph-level Topic Representation, Corpus, and Benchmark

1 code implementation24 May 2023 Feng Jiang, Weihao Liu, Xiaomin Chu, Peifeng Li, Qiaoming Zhu, Haizhou Li

Topic segmentation and outline generation strive to divide a document into coherent topic sections and generate corresponding subheadings, unveiling the discourse topic structure of a document.

Discourse Parsing Information Retrieval +2

Cannot find the paper you are looking for? You can Submit a new open access paper.