6 citations · 8 across the 4 of their papers we have counts for
4 papers
MMAT-1M: A Large Reasoning Dataset for Multimodal Agent Tuning
Tianhong Gao, Yannian Fu, Weiqun Wu +3
Large Language Models (LLMs), enhanced through agent tuning, have demonstrated remarkable capabilities in Chain-of-Thought (CoT) and tool utilization, significantly surpassing the…
Knowledge Distillation with Training Wheels
Guanlin Liu, Anand Ramachandran, Tanmay Gangwani +2
Knowledge distillation is used, in generative language modeling, to train a smaller student model using the help of a larger teacher model, resulting in improved capabilities for t…
Reinforced Multi-Teacher Selection for Knowledge Distillation
Fei Yuan, Linjun Shou, Jian Pei +4
In natural language processing (NLP) tasks, slow inference speed and huge footprints in GPU usage remain the bottleneck of applying pre-trained deep models in production. As a popu…
Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension
Fei Yuan, Linjun Shou, Xuanyu Bai +5
Multilingual pre-trained models could leverage the training data from a rich source language (such as English) to improve performance on low resource languages. However, the transf…