2 papers
cs.AI2026
JUMP: Single-Pass Membership Inference on Fine-Tuned Diffusion Language Models
Yeachan Jun, Albert No
Public open-weight language models are often fine-tuned on private or domain-specific data before deployment, creating a need to audit whether individual records were used during a…
cs.CL2026
Position: The Term "Machine Unlearning" Is Overused in LLMs
Sangyeon Yoon, Yeachan Jun, Albert No
Large language models increasingly face demands to "forget" training data, knowledge, or behaviors due to regulatory deletion obligations, copyright/licensing disputes, and safety…