17 citations · 36 across the 8 of their papers we have counts for
8 papers
MathMixup: Boosting LLM Mathematical Reasoning with Difficulty-Controllable Data Synthesis and Curriculum Learning
Xuchen Li, Jing Chen, Xuzhao Li +4
In mathematical reasoning tasks, the advancement of Large Language Models (LLMs) relies heavily on high-quality training data with clearly defined and well-graded difficulty levels…
xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data
Jing Gong, Minsheng Hao, Xingyi Cheng +6
Advances in high-throughput sequencing technology have led to significant progress in measuring gene expressions at the single-cell level. The amount of publicly available single-c…
Drug Synergistic Combinations Predictions via Large-Scale Pre-Training and Graph Structure Learning
Zhihang Hu, Qinze Yu, Yucheng Guo +5
Drug combination therapy is a well-established strategy for disease treatment with better effectiveness and less safety degradation. However, identifying novel drug combinations th…
PIE: a Parameter and Inference Efficient Solution for Large Scale Knowledge Graph Embedding Reasoning
Linlin Chao, Xiexiong Lin, Taifeng Wang +1
Knowledge graph (KG) embedding methods which map entities and relations to unique embeddings in the KG have shown promising results on many reasoning tasks. However, the same embed…
Keywords and Instances: A Hierarchical Contrastive Learning Framework Unifying Hybrid Granularities for Text Generation
Mingzhe Li, XieXiong Lin, Xiuying Chen +8
Contrastive learning has achieved impressive success in generation tasks to militate the "exposure bias" problem and discriminatively exploit the different quality of references. E…
PairRE: Knowledge Graph Embeddings via Paired Relation Vectors
Linlin Chao, Jianshan He, Taifeng Wang +1
Distance based knowledge graph embedding methods show promising results on link prediction task, on which two topics have been widely studied: one is the ability to handle complex…
Question Directed Graph Attention Network for Numerical Reasoning over Text
Kunlong Chen, Weidi Xu, Xingyi Cheng +6
Numerical reasoning over texts, such as addition, subtraction, sorting and counting, is a challenging machine reading comprehension task, since it requires both natural language un…
Overview of the CCKS 2019 Knowledge Graph Evaluation Track: Entity, Relation, Event and QA
Xianpei Han, Zhichun Wang, Jiangtao Zhang +22
Knowledge graph models world knowledge as concepts, entities, and the relationships between them, which has been widely used in many real-world tasks. CCKS 2019 held an evaluation…