5 citations · 25 across the 33 of their papers we have counts for
11 papers · 2 filters
CMM-Math: A Chinese Multimodal Math Dataset To Evaluate and Enhance the Mathematics Reasoning of Large Multimodal Models
Wentao Liu, Qianjun Pan, Yi Zhang +7
Large language models (LLMs) have obtained promising results in mathematical reasoning, which is a foundational skill for human intelligence. Most previous studies focus on improvi…
Boosting Large Language Models with Socratic Method for Conversational Mathematics Teaching
Yuyang Ding, Hanglei Hu, Jie Zhou +3
With the introduction of large language models (LLMs), automatic math reasoning has seen tremendous success. However, current methods primarily focus on providing solutions or usin…
P-React: Synthesizing Topic-Adaptive Reactions of Personality Traits via Mixture of Specialized LoRA Experts
Yuhao Dan, Jie Zhou, Qin Chen +2
Personalized large language models (LLMs) have attracted great attention in many applications, such as emotional support and role-playing. However, existing works primarily focus o…
Modeling Comparative Logical Relation with Contrastive Learning for Text Generation
Yuhao Dan, Junfeng Tian, Jie Zhou +4
Data-to-Text Generation (D2T), a classic natural language generation problem, aims at producing fluent descriptions for structured input data, such as a table. Existing D2T works m…
Boosting Large Language Models with Continual Learning for Aspect-based Sentiment Analysis
Xuanwen Ding, Jie Zhou, Liang Dou +4
Aspect-based sentiment analysis (ABSA) is an important subtask of sentiment analysis, which aims to extract the aspects and predict their sentiments. Most existing studies focus on…
Recent Advances of Foundation Language Models-based Continual Learning: A Survey
Yutao Yang, Jie Zhou, Xuanwen Ding +5
Recently, foundation language models (LMs) have marked significant achievements in the domains of natural language processing (NLP) and computer vision (CV). Unlike traditional neu…