4 citations · 5 across the 10 of their papers we have counts for
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cs.AI2024★ 1 cited
Can Large Language Models Understand DL-Lite Ontologies? An Empirical Study
Keyu Wang, Guilin Qi, Jiaqi Li +1
Large language models (LLMs) have shown significant achievements in solving a wide range of tasks. Recently, LLMs' capability to store, retrieve and infer with symbolic knowledge h…
cs.CV2024★ 4 cited
Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models
Jiaqi Li, Qianshan Wei, Chuanyi Zhang +5
Machine unlearning empowers individuals with the `right to be forgotten' by removing their private or sensitive information encoded in machine learning models. However, it remains…
cs.CL2024
MIKE: A New Benchmark for Fine-grained Multimodal Entity Knowledge Editing
Jiaqi Li, Miaozeng Du, Chuanyi Zhang +6
Multimodal knowledge editing represents a critical advancement in enhancing the capabilities of Multimodal Large Language Models (MLLMs). Despite its potential, current benchmarks…