Publications

ICLR'25 Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning.
Tianci Liu, Ruirui Li, Yunzhe Qi, Hui Liu, Xianfeng Tang, Tianqi Zheng, Qingyu Yin, Monica Cheng, Jun Huan, Haoyu Wang, Jing Gao.

SenSys'25 URAM-Hand: Robust Acoustic Multi-Hand Pose Reconstruction Using a Microphone Array.
Shiyang Wang, Henglin Pu, Qiming Cao, Wenjun Jiang, Xingchen Wang, Tianci Liu, Zhengxin Jiang, Hongfei Xue, Lu Su.

NeurIPS'24 FIARSE: Model-Heterogeneity Federated Learning via Importance-Aware Submodel Extraction.
Feijie Wu, Xingchen Wang, Yaqing Wang, Tianci Liu, Lu Su, Jing Gao.

NeurIPS'24 Counterfactual Fairness by Combining Factual and Counterfactual Predictions.
Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David Inouye.

EMNLP'24 RoseLoRA: Row and Column-wise Sparse Low-Rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning.
Haoyu Wang, Tianci Liu, Ruirui Li, Monica Cheng, Tuo Zhao, Jing Gao.
(Oral, 2.8%)

SenSys'24 mmCLIP: Boosting mmWave-based Zero-shot HAR via Signal-Text Alignment.
Qiming Cao, Hongfei Xue, Tianci Liu, Xingchen Wang, Haoyu Wang, Xincheng Zhang, Lu Su.

SenSys'24 Towards Efficient Heterogeneous Multi-Modal Federated Learning with Hierarchical Knowledge Disentanglement.
Xingchen Wang, Haoyu Wang, Feijie Wu, Tianci Liu, Qiming Cao, Lu Su.

ICML'24 LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models.
Tianci Liu, Haoyu Wang, Shiyang Wang, Yu Cheng, Jing Gao
(Spotlight, 3.5%)

ICLR'24 Towards Poisoning Fair Representations.
Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao.

EMNLP'23 Findings HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference.
Haoyu Wang, Yaqing Wang, Tianci Liu, Tuo Zhao, Jing Gao.

AAAI'23 SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification.
Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao.
(Distinguished Paper Award, 12 out of 8777 submissions)

ICML'23 Optimization for Amortized Inverse Problems.
Tianci Liu*, Tong Yang*, Quan Zhang, Qi Lei (Equal Contribution).

Stat Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks.
Daiwei Zhang, Tianci Liu, Jian Kang.

Scientific Reports Physically informed machine-learning algorithms for the identification of two-dimensional atomic crystals.
Laura Zichi, Tianci Liu, Elizabeth Drueke, Liuyan Zhao, and Gongjun Xu.

Frontiers in Psychology Estimating three- and four-parameter MIRT models with importance-weighted sampling enhanced variational auto-encoder.
Tianci Liu, Chun Wang, Gongjun Xu.

2021