3 papers
cs.CV2026
Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models
Yuwen Tan, Boqing Gong
Machine unlearning removes certain training data points and their influence from AI models (e.g., when a data owner revokes their consent to allow models to learn from the data). I…
cs.CV2026
The LLM Bottleneck: Why Open-Source Vision LLMs Struggle with Hierarchical Visual Recognition
Yuwen Tan, Yuan Qing, Boqing Gong
This paper reveals that many open-source large language models (LLMs) lack hierarchical knowledge about our visual world, unaware of even well-established biology taxonomies. This…
cs.CV2025
Continual Adapter Tuning with Semantic Shift Compensation for Class-Incremental Learning
Qinhao Zhou, Yuwen Tan, Boqing Gong +1
Class-incremental learning (CIL) aims to enable models to continuously learn new classes while overcoming catastrophic forgetting. The introduction of pre-trained models has brough…