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JingSheng Liu

2 accepted papers

2026

Dual-Prototype-Guided Multi-task Learning for Unsupervised Anomaly Detection and Classification

CVPR 2026

Unsupervised Anomaly Detection (UAD) and anomaly classification are frequently used in industrial and medical scenarios. Specifically, UAD identifies anomalous regions at the fine-grained pixel-level, while anomaly classification distinguishes anomaly types at the anomaly region level. However, exis

Cited by 0SourcecodeScholar
2025

Correlated Low-Rank Adaptation for ConvNets

NeurIPS 2025poster

Low-Rank Adaptation (LoRA) methods have demonstrated considerable success in achieving parameter-efficient fine-tuning (PEFT) for Transformer-based foundation models. These methods typically fine-tune individual Transformer layers using independent LoRA adaptations. However, directly applying existi…

Cited by 0SourcecodeScholar