4 papers · 1 filter
Accelerate Scaling of LLM Finetuning via Quantifying the Coverage and Depth of Instruction Set
Chengwei Wu, Li Du, Hanyu Zhao +4
Scaling the amount of data used for supervied fine-tuning(SFT) does not guarantee the proportional gains in model performance, highlighting a critical need to understand what makes…
CI-VID: A Coherent Interleaved Text-Video Dataset
Yiming Ju, Jijin Hu, Zhengxiong Luo +7
Text-to-video (T2V) generation has recently attracted considerable attention, resulting in the development of numerous high-quality datasets that have propelled progress in this ar…
Scaling Towards the Information Boundary of Instruction Sets: The Infinity Instruct Subject Technical Report
Li Du, Hanyu Zhao, Yiming Ju +1
Instruction tuning has become a foundation for unlocking the capabilities of large-scale pretrained models and improving their performance on complex tasks. Thus, the construction…
Infinity Instruct: Scaling Instruction Selection and Synthesis to Enhance Language Models
Jijie Li, Li Du, Hanyu Zhao +5
Large Language Models (LLMs) demonstrate strong performance in real-world applications, yet existing open-source instruction datasets often concentrate on narrow domains, such as m…