7 papers
Conformal Reliability: A New Evaluation Metric for Conditional Generation
Yachen Gao, Xinwei Sun, Yikai Wang +4
Conditional generative models have recently achieved remarkable success in various applications. However, a suitable metric for evaluating the reliability of these models, which ta…
Causal Inference for Network Autoregression Model: A Targeted Minimum Loss Estimation Approach
Yong Wu, Shuyuan Wu, Xinwei Sun +1
We study estimation of the average treatment effect (ATE) from a single network in observational settings with interference. The weak cross-unit dependence is modeled via an endoge…
Discovering Causal Relationships using Proxy Variables under Unmeasured Confounding
Yong Wu, Yanwei Fu, Shouyan Wang +2
Inferring causal relationships between variable pairs in the observational study is crucial but challenging, due to the presence of unmeasured confounding. While previous methods e…
Towards Reliable and Holistic Visual In-Context Learning Prompt Selection
Wenxiao Wu, Jing-Hao Xue, Chengming Xu +5
Visual In-Context Learning (VICL) has emerged as a prominent approach for adapting visual foundation models to novel tasks, by effectively exploiting contextual information embedde…
Revisiting Large Language Model Pruning using Neuron Semantic Attribution
Yizhuo Ding, Xinwei Sun, Yanwei Fu +1
Model pruning technique is vital for accelerating large language models by reducing their size and computational requirements. However, the generalizability of existing pruning met…
Adaptive Pruning of Pretrained Transformer via Differential Inclusions
Yizhuo Ding, Ke Fan, Yikai Wang +2
Large transformers have demonstrated remarkable success, making it necessary to compress these models to reduce inference costs while preserving their perfor-mance. Current compres…