2 citations · 2 across the 6 of their papers we have counts for
7 papers
Open-MMUnlearning: Unifying Methods and Evaluation for MLLM Unlearning
Junkai Chen, Yuhao He, Qianshan Wei +19
As multimodal large language models (MLLMs) become more capable and widely deployed, concerns about privacy and safety have become increasingly pressing. Machine unlearning offers…
Exploring and Bridging Knowledge Holes in Unlearned Multimodal Large Language Models
Junxiang You, Junkai Chen, Yuhao He +3
Machine unlearning offers a promising approach to remove unsafe content from Multimodal Large Language Models (MLLMs), yet ensuring the precision of unlearning remains a persistent…
Toward Fine-Grained Forgetting:Attribute Unlearning for Multimodal Large Language Models
Junkai Lin, Junkai Chen, Siqi Hou +6
Multimodal large language models (MLLMs) can memorize and disclose sensitive information, motivating machine unlearning to remove designated knowledge while preserving model utilit…
UNISON: A Unified Sound Generation and Editing Framework via Deep LLM Fusion
Zhaoqing Li, Haoning Xu, Jingran Su +9
We present UNISON, a latent diffusion framework that unifies speech generation, sound generation, and audio editing within a single model. A single model handles text-to-audio, tex…
Visual-Noise Guided In-Context Distillation for Multimodal Large Language Model Unlearning
Junkai Chen, Yuhao He, Junxiang You +3
Multimodal Large Language Models (MLLMs) have achieved remarkable progress on vision-language tasks, but they may also memorize and expose sensitive or restricted knowledge, raisin…
How Far Is Document Parsing from Solved? PureDocBench: A Source-Traceable Benchmark across Clean, Degraded, and Real-World Settings
Zhiheng Li, Zongyang Ma, Jiaxian Chen +12
Document parsing models are improving rapidly, but existing benchmarks are still insufficient for a comprehensive evaluation of their capabilities. We introduce PureDocBench, a ben…
Fast On-device LLM Inference with NPUs
Daliang Xu, Hao Zhang, Liming Yang +4
On-device inference for Large Language Models (LLMs), driven by increasing privacy concerns and advancements of mobile-sized models, has gained significant interest. However, even…