1 citations · 2 across the 8 of their papers we have counts for
10 papers
AviationLMM: A Large Multimodal Foundation Model for Civil Aviation
Wenbin Li, Jingling Wu, Xiaoyong Lin. Jing Chen +1
Civil aviation is a cornerstone of global transportation and commerce, and ensuring its safety, efficiency and customer satisfaction is paramount. Yet conventional Artificial Intel…
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…
OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
Ben Chen, Xian Guo, Siyuan Wang +25
Traditional e-commerce search systems employ multi-stage cascading architectures (MCA) that progressively filter items through recall, pre-ranking, and ranking stages. While effect…
Self-evolved Imitation Learning in Simulated World
Yifan Ye, Jun Cen, Jing Chen +1
Imitation learning has been a trend recently, yet training a generalist agent across multiple tasks still requires large-scale expert demonstrations, which are costly and labor-int…
SurveyGen-I: Consistent Scientific Survey Generation with Evolving Plans and Memory-Guided Writing
Jing Chen, Zhiheng Yang, Yixian Shen +4
Survey papers play a critical role in scientific communication by consolidating progress across a field. Recent advances in Large Language Models (LLMs) offer a promising solution…
Hide and Seek with LLMs: An Adversarial Game for Sneaky Error Generation and Self-Improving Diagnosis
Rui Zou, Mengqi Wei, Yutao Zhu +3
Large Language Models (LLMs) excel in reasoning and generation across domains, but still struggle with identifying and diagnosing complex errors. This stems mainly from training ob…