21 citations · 53 across the 15 of their papers we have counts for
5 papers · 1 filter
Can We Edit Multimodal Large Language Models?
Siyuan Cheng, Bozhong Tian, Qingbin Liu +4
In this paper, we focus on editing Multimodal Large Language Models (MLLMs). Compared to editing single-modal LLMs, multimodal model editing is more challenging, which demands a hi…
EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models
Peng Wang, Ningyu Zhang, Bozhong Tian +11
Large Language Models (LLMs) usually suffer from knowledge cutoff or fallacy issues, which means they are unaware of unseen events or generate text with incorrect facts owing to ou…
Editing Large Language Models: Problems, Methods, and Opportunities
Yunzhi Yao, Peng Wang, Bozhong Tian +5
Despite the ability to train capable LLMs, the methodology for maintaining their relevancy and rectifying errors remains elusive. To this end, the past few years have witnessed a s…
Revisiting k-NN for Fine-tuning Pre-trained Language Models
Lei Li, Jing Chen, Bozhong Tian +1
Pre-trained Language Models (PLMs), as parametric-based eager learners, have become the de-facto choice for current paradigms of Natural Language Processing (NLP). In contrast, k-N…
Editing Language Model-based Knowledge Graph Embeddings
Siyuan Cheng, Ningyu Zhang, Bozhong Tian +3
Recently decades have witnessed the empirical success of framing Knowledge Graph (KG) embeddings via language models. However, language model-based KG embeddings are usually deploy…