Tianci Liu

36 papers A* 9A 1Misc 3Journal 17Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training.
CoRR
Ran Xu, Tianci Liu, Zihan Dong, Tony Yu, Ilgee Hong, Carl Yang, Linjun Zhang, Tao Zhao, Haoyu Wang
2026 — conf
PEANuT: Parameter-Efficient Adaptation with Weight-aware Neural Tweakers.
KDD (1)
Yibo Zhong, Haoxiang Jiang, Lincan Li, Ryumei Nakada, Tianci Liu, Linjun Zhang, Huaxiu Yao, Haoyu Wang
2025 A conf
Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection.
UAI
Tianci Liu, Tong Yang, Quan Zhang, Qi Lei
2025 J jnl
Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection.
CoRR
Tianci Liu, Tong Yang, Quan Zhang, Qi Lei
2025 — conf
Learning to Instruct: Fine-Tuning a Task-Aware Instruction Optimizer for Black-Box LLMs.
EMNLP (Findings)
Yunzhe Qi, Jinjin Tian, Tianci Liu, Ruirui Li, Tianxin Wei, Hui Liu, Xianfeng Tang, Monica Xiao Cheng, Jingrui He
2025 A* conf
Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing.
ICML
Tianci Liu, Ruirui Li, Zihan Dong, Hui Liu, Xianfeng Tang, Qingyu Yin, Linjun Zhang, Haoyu Wang, Jing Gao
2025 J jnl
Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing.
CoRR
Tianci Liu, Zihan Dong, Linjun Zhang, Haoyu Wang, Jing Gao
2025 J jnl
OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment.
CoRR
Tianci Liu, Ran Xu, Tony Yu, Ilgee Hong, Carl Yang, Tuo Zhao, Haoyu Wang
2025 Misc conf
RAM-Hand: Robust Acoustic Multi-Hand Pose Reconstruction Using a Microphone Array.
SenSys
Shiyang Wang, Henglin Pu, Qiming Cao, Wenjun Jiang, Xingchen Wang, Tianci Liu, Zhengxin Jiang, Hongfei Xue, Lu Su
2025 — conf
RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization.
ACL (Findings)
Tianci Liu, Haoxiang Jiang, Tianze Wang, Ran Xu, Yue Yu, Linjun Zhang, Tuo Zhao, Haoyu Wang
2025 J jnl
RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization.
CoRR
Tianci Liu, Haoxiang Jiang, Tianze Wang, Ran Xu, Yue Yu, Linjun Zhang, Tuo Zhao, Haoyu Wang
2025 — conf
Toward Generalizable, General-Purpose, and Multimodal Knowledge Editing for Foundation Models.
ICDM (Workshops)
Haoyu Wang, Tianci Liu, Fenglong Ma, Jing Gao
2025 — conf
Towards Universal Debiasing for Language Models-based Tabular Data Generation.
EMNLP (Findings)
Tianchun Li, Tianci Liu, Xingchen Wang, Rongzhe Wei, Pan Li, Lu Su, Jing Gao
2025 J jnl
Towards Universal Debiasing for Language Models-based Tabular Data Generation.
CoRR
Tianchun Li, Tianci Liu, Xingchen Wang, Rongzhe Wei, Pan Li, Lu Su, Jing Gao
2025 A* conf
Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning.
ICLR
Tianci Liu, Ruirui Li, Yunzhe Qi, Hui Liu, Xianfeng Tang, Tianqi Zheng, Qingyu Yin, Monica Xiao Cheng, Jun Huan, Haoyu Wang, Jing Gao
2025 J jnl
Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning.
CoRR
Tianci Liu, Ruirui Li, Yunzhe Qi, Hui Liu, Xianfeng Tang, Tianqi Zheng, Qingyu Yin, Monica Xiao Cheng, Jun Huan, Haoyu Wang, Jing Gao
2024 A* conf
Counterfactual Fairness by Combining Factual and Counterfactual Predictions.
NeurIPS
Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David I. Inouye
2024 J jnl
Counterfactual Fairness by Combining Factual and Counterfactual Predictions.
CoRR
Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David I. Inouye
2024 A* conf
FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction.
NeurIPS
Feijie Wu, Xingchen Wang, Yaqing Wang, Tianci Liu, Lu Su, Jing Gao
2024 J jnl
FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction.
CoRR
Feijie Wu, Xingchen Wang, Yaqing Wang, Tianci Liu, Lu Su, Jing Gao
2024 A* conf
LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models.
ICML
Tianci Liu, Haoyu Wang, Shiyang Wang, Yu Cheng, Jing Gao
2024 J jnl
LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models.
CoRR
Tianci Liu, Haoyu Wang, Shiyang Wang, Yu Cheng, Jing Gao
2024 J jnl
NEAT: Nonlinear Parameter-efficient Adaptation of Pre-trained Models.
CoRR
Yibo Zhong, Haoxiang Jiang, Lincan Li, Ryumei Nakada, Tianci Liu, Linjun Zhang, Huaxiu Yao, Haoyu Wang
2024 A* conf
RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning.
EMNLP
Haoyu Wang, Tianci Liu, Ruirui Li, Monica Xiao Cheng, Tuo Zhao, Jing Gao
2024 J jnl
RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning.
CoRR
Haoyu Wang, Tianci Liu, Tuo Zhao, Jing Gao
2024 Misc conf
Towards Efficient Heterogeneous Multi-Modal Federated Learning with Hierarchical Knowledge Disentanglement.
SenSys
Xingchen Wang, Haoyu Wang, Feijie Wu, Tianci Liu, Qiming Cao, Lu Su
2024 A* conf
Towards Poisoning Fair Representations.
ICLR
Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao
2024 Misc conf
mmCLIP: Boosting mmWave-based Zero-shot HAR via Signal-Text Alignment.
SenSys
Qiming Cao, Hongfei Xue, Tianci Liu, Xingchen Wang, Haoyu Wang, Xincheng Zhang, Lu Su
2023 — conf
HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference.
EMNLP (Findings)
Haoyu Wang, Yaqing Wang, Tianci Liu, Tuo Zhao, Jing Gao
2023 A* conf
Optimization for Amortized Inverse Problems.
ICML
Tianci Liu, Tong Yang, Quan Zhang, Qi Lei
2023 A* conf
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification.
AAAI
Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao
2023 J jnl
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification.
CoRR
Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao
2023 J jnl
Towards Poisoning Fair Representations.
CoRR
Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao
2022 J jnl
COEP: Cascade Optimization for Inverse Problems with Entropy-Preserving Hyperparameter Tuning.
CoRR
Tianci Liu, Tong Yang, Quan Zhang, Qi Lei
2022 J jnl
Density Regression and Uncertainty Quantification with Bayesian Deep Noise Neural Networks.
CoRR
Daiwei Zhang, Tianci Liu, Jian Kang
2020 J jnl
Flows Succeed Where GANs Fail: Lessons from Low-Dimensional Data.
CoRR
Tianci Liu, Jeffrey Regier