3 citations · 7 across the 10 of their papers we have counts for
5 papers · 1 filter
Distribution Corrected Offline Data Distillation for Large Language Models
Yumeng Zhang, Zhengbang Yang, Yevin Nikhel Goonatilake +1
Distilling reasoning traces from strong large language models into smaller ones is a promising route to improve intelligence in resource-constrained settings. Existing approaches f…
CALIBURN: Self-Calibrated LLM Unlearning Alignment
Zhengbang Yang, Yisheng Zhong, Junyuan Hong +1
LLM unlearning aims to remove the influence of undesirable knowledge from pretrained language models, which offers a practical mechanism for addressing safety and privacy concerns.…
Sports Intelligence: Assessing the Sports Understanding Capabilities of Language Models through Question Answering from Text to Video
Zhengbang Yang, Haotian Xia, Jingxi Li +3
Understanding sports is crucial for the advancement of Natural Language Processing (NLP) due to its intricate and dynamic nature. Reasoning over complex sports scenarios has posed…
Language and Multimodal Models in Sports: A Survey of Datasets and Applications
Haotian Xia, Zhengbang Yang, Yun Zhao +7
Recent integration of Natural Language Processing (NLP) and multimodal models has advanced the field of sports analytics. This survey presents a comprehensive review of the dataset…
SportQA: A Benchmark for Sports Understanding in Large Language Models
Haotian Xia, Zhengbang Yang, Yuqing Wang +7
A deep understanding of sports, a field rich in strategic and dynamic content, is crucial for advancing Natural Language Processing (NLP). This holds particular significance in the…