X Cheng, Z Yao, Y Xin, H An, H Li, Y Li… - Proceedings of the 62nd …, 2024 - aclanthology.org
Multimodal machine translation (MMT) aims to improve the performance of machine translation with the help of visual information, which has received widespread attention …
We present Self-MoE, an approach that transforms a monolithic LLM into a compositional, modular system of self-specialized experts, named MiXSE (MiXture of Self-specialized …
A Alexandrov, V Raychev, MN Müller, C Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
As open-weight large language models (LLMs) achieve ever more impressive performances across a wide range of tasks in English, practitioners aim to adapt these models to different …
J Zheng, S Qiu, C Shi, Q Ma - arXiv preprint arXiv:2406.06391, 2024 - arxiv.org
As the applications of large language models (LLMs) expand across diverse fields, the ability of these models to adapt to ongoing changes in data, tasks, and user preferences …
G Jiang, Z Li, C Jiang, S Xue, J Zhou, L Song… - arXiv preprint arXiv …, 2024 - arxiv.org
Fine-tuning large language models (LLMs) can cause them to lose their general capabilities. However, the intrinsic mechanisms behind such forgetting remain unexplored. In this paper …
Y Feng, X Chu, Y Xu, Z Lu, B Liu, PS Yu… - arXiv preprint arXiv …, 2024 - arxiv.org
Language model continual learning (CL) has recently garnered significant interest due to its potential to adapt large language models (LLMs) to dynamic real-world environments …
Inspired by the rapid development of Large Language Models (LLMs), LLM agents have evolved to perform complex tasks. LLM agents are now extensively applied across various …
Incremental learning is the ability of systems to acquire knowledge over time, enabling their adaptation and generalization to novel tasks. It is a critical ability for intelligent, real-world …