collaborators

5 papers

cs.GR2026

CASteer: Cross-Attention Steering for Controllable Concept Erasure

Tatiana Gaintseva, Andreea-Maria Oncescu, Chengcheng Ma +5

Diffusion models have transformed image generation, yet controlling their outputs to reliably erase undesired concepts remains challenging. Existing approaches usually require task…

cs.LG2025

Cost-Sensitive Conformal Training with Provably Controllable Learning Bounds

Xuesong Jia, Yuanjie Shi, Ziquan Liu +2

Conformal prediction (CP) is a general framework to quantify the predictive uncertainty of machine learning models that uses a set prediction to include the true label with a valid…

cs.LG2025

Learning Multi-Timescale Interventions under Safety and Resource Constraints

David H. Mguni, David Mguni, Jing Dong +6

Many sequential decision problems offer qualitatively different ways of influencing the environment: some interventions act immediately, whereas others induce persistent effects th…

cs.CV2025

ConformalSAM: Unlocking the Potential of Foundational Segmentation Models in Semi-Supervised Semantic Segmentation with Conformal Prediction

Danhui Chen, Ziquan Liu, Chuxi Yang +4

Pixel-level vision tasks, such as semantic segmentation, require extensive and high-quality annotated data, which is costly to obtain. Semi-supervised semantic segmentation (SSSS)…

cs.LG2025

Query-based Knowledge Transfer for Heterogeneous Learning Environments

Norah Alballa, Wenxuan Zhang, Ziquan Liu +3

Decentralized collaborative learning under data heterogeneity and privacy constraints has rapidly advanced. However, existing solutions like federated learning, ensembles, and tran…