1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2024
CharacterBox: Evaluating the Role-Playing Capabilities of LLMs in Text-Based Virtual Worlds
Lei Wang, Jianxun Lian, Yi Huang +5
Role-playing is a crucial capability of Large Language Models (LLMs), enabling a wide range of practical applications, including intelligent non-player characters, digital twins, a…
cs.CV2024
Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of Experts
Jinqiang Long, Yanqi Dai, Guoxing Yang +4
As the research of Multimodal Large Language Models (MLLMs) becomes popular, an advancing MLLM model is typically required to handle various textual and visual tasks (e.g., VQA, De…
cs.LG2023★ 1 cited
Improvable Gap Balancing for Multi-Task Learning
Yanqi Dai, Nanyi Fei, Zhiwu Lu
In multi-task learning (MTL), gradient balancing has recently attracted more research interest than loss balancing since it often leads to better performance. However, loss balanci…