Real-time learning concerns the ability of learning systems to acquire knowledge over time,
enabling their adaptation and generalization to novel tasks. It is a critical ability for …

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 …

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 …

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 …

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 …

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 …