4 citations · 9 across the 5 of their papers we have counts for
5 papers
Learning from Peers in Reasoning Models
Tongxu Luo, Wenyu Du, Jiaxi Bi +5
Large Reasoning Models (LRMs) have the ability to self-correct even when they make mistakes in their reasoning paths. However, our study reveals that when the reasoning process sta…
MoELoRA: Contrastive Learning Guided Mixture of Experts on Parameter-Efficient Fine-Tuning for Large Language Models
Tongxu Luo, Jiahe Lei, Fangyu Lei +4
Fine-tuning is often necessary to enhance the adaptability of Large Language Models (LLM) to downstream tasks. Nonetheless, the process of updating billions of parameters demands s…
TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering
Fangyu Lei, Tongxu Luo, Pengqi Yang +8
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…
HRoT: Hybrid prompt strategy and Retrieval of Thought for Table-Text Hybrid Question Answering
Tongxu Luo, Fangyu Lei, Jiahe Lei +4
Answering numerical questions over hybrid contents from the given tables and text(TextTableQA) is a challenging task. Recently, Large Language Models (LLMs) have gained significant…
MMHQA-ICL: Multimodal In-context Learning for Hybrid Question Answering over Text, Tables and Images
Weihao Liu, Fangyu Lei, Tongxu Luo +4
In the real world, knowledge often exists in a multimodal and heterogeneous form. Addressing the task of question answering with hybrid data types, including text, tables, and imag…