1 citations · 1 across the 3 of their papers we have counts for
5 papers
Representation Calibration and Uncertainty Guidance for Class-Incremental Learning based on Vision Language Model
Jiantao Tan, Peixian Ma, Tong Yu +2
Class-incremental learning requires a learning system to continually learn knowledge of new classes and meanwhile try to preserve previously learned knowledge of old classes. As cu…
Augmenting Continual Learning of Diseases with LLM-Generated Visual Concepts
Jiantao Tan, Peixian Ma, Kanghao Chen +2
Continual learning is essential for medical image classification systems to adapt to dynamically evolving clinical environments. The integration of multimodal information can signi…
Effective Learning for Small Reasoning Models: An Empirical Study on 0.5B Reasoning LLMs
Xialie Zhuang, Peixian Ma, Zhikai Jia +2
The ongoing evolution of language models has led to the development of large-scale architectures that demonstrate exceptional performance across a wide range of tasks. However, the…
SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning
Peixian Ma, Xialie Zhuang, Chengjin Xu +3
Natural Language to SQL (NL2SQL) enables intuitive interactions with databases by transforming natural language queries into structured SQL statements. Despite recent advancements…
A Plug-and-Play Natural Language Rewriter for Natural Language to SQL
Peixian Ma, Boyan Li, Runzhi Jiang +3
Existing Natural Language to SQL (NL2SQL) solutions have made significant advancements, yet challenges persist in interpreting and translating NL queries, primarily due to users' l…