Tianci Liu

According to our database, Tianci Liu authored at least 20 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing.

Tianci Liu, Zihan Dong, Linjun Zhang, Haoyu Wang, Jing Gao

CoRR, February, 2025

Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection.

Tianci Liu, Tong Yang, Quan Zhang, Qi Lei

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

RAM-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

Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems, 2025

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 Xiao Cheng, Jun Huan, Haoyu Wang, Jing Gao

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization.

Tianci Liu, Haoxiang Jiang, Tianze Wang, Ran Xu, Yue Yu, Linjun Zhang, Tuo Zhao, Haoyu Wang

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

NEAT: Nonlinear Parameter-efficient Adaptation of Pre-trained Models.

Yibo Zhong, Haoxiang Jiang, Lincan Li, Ryumei Nakada, Tianci Liu, Linjun Zhang, Huaxiu Yao, Haoyu Wang

CoRR, 2024

RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning.

Haoyu Wang, Tianci Liu, Tuo Zhao, Jing Gao

CoRR, 2024

Towards Efficient Heterogeneous Multi-Modal Federated Learning with Hierarchical Knowledge Disentanglement.

Xingchen Wang, Haoyu Wang, Feijie Wu, Tianci Liu, Qiming Cao, Lu Su

Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems, 2024

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

Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems, 2024

Counterfactual Fairness by Combining Factual and Counterfactual Predictions.

Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David I. Inouye

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction.

Feijie Wu, Xingchen Wang, Yaqing Wang, Tianci Liu, Lu Su, Jing Gao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models.

Tianci Liu, Haoyu Wang, Shiyang Wang, Yu Cheng, Jing Gao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Poisoning Fair Representations.

Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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 Xiao Cheng, Tuo Zhao, Jing Gao

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Optimization for Amortized Inverse Problems.

Tianci Liu, Tong Yang, Quan Zhang, Qi Lei

Proceedings of the International Conference on Machine Learning, 2023

HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference.

Haoyu Wang, Yaqing Wang, Tianci Liu, Tuo Zhao, Jing Gao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification.

Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

COEP: Cascade Optimization for Inverse Problems with Entropy-Preserving Hyperparameter Tuning.

Tianci Liu, Tong Yang, Quan Zhang, Qi Lei

CoRR, 2022

Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks.

Daiwei Zhang, Tianci Liu, Jian Kang

CoRR, 2022

2020

Flows Succeed Where GANs Fail: Lessons from Low-Dimensional Data.

Tianci Liu, Jeffrey Regier

CoRR, 2020