Lingzhi Wang

54 papers A* 7A 1B 4Journal 27Unranked 15
YearRankTypeTitle / Venue / Authors
2026 J jnl
ARTIS: Agentic Risk-Aware Test-Time Scaling via Iterative Simulation.
CoRR
Xingshan Zeng, Lingzhi Wang, Weiwen Liu, Liangyou Li, Yasheng Wang, Lifeng Shang, Xin Jiang, Qun Liu
2026 — conf
Improving Heterogeneous Graph Contrastive Learning Robustness via Hierarchical Vulnerability Protection.
KDD (1)
Jinhao Cui, Chaoyang Li, Jianyang Qin, Lingzhi Wang, Cuiyun Gao, Qing Liao
2026 A* conf
ToolACE-R: Model-aware Iterative Training and Adaptive Refinement for Tool learning.
AAAI
Xingshan Zeng, Weiwen Liu, Xu Huang, Zezhong Wang, Lingzhi Wang, Liangyou Li, Yasheng Wang, Lifeng Shang, Xin Jiang, Ruiming Tang, Qun Liu
2025 A* conf
Adaptive Data and Task Joint Scheduling for Multi-Task Learning.
ICDE
Zeyu Liu, Heyan Chai, Chaoyang Li, Lingzhi Wang, Qing Liao
2025 A* conf
CoMaPOI: A Collaborative Multi-Agent Framework for Next POI Prediction Bridging the Gap Between Trajectory and Language.
SIGIR
Lin Zhong, Lingzhi Wang, Xu Yang, Qing Liao
2025 J jnl
CoMaPOI: A Collaborative Multi-Agent Framework for Next POI Prediction Bridging the Gap Between Trajectory and Language.
CoRR
Lin Zhong, Lingzhi Wang, Xu Yang, Qing Liao
2025 J jnl
Counterspeech for Mitigating the Influence of Media Bias: Comparing Human and LLM-Generated Responses.
CoRR
Luyang Lin, Zijin Feng, Lingzhi Wang, Kam-Fai Wong
2025 — conf
Cross-Modal Causal Scheduling for Enhancing Target-Oriented Multi-modal Sentiment Classification.
ECML/PKDD (4)
Pengyu Zhao, Chaoyang Li, Lingzhi Wang, Qing Liao
2025 J jnl
DA-PFL: Dynamic Affinity Aggregation in Personalized Federated Learning Under Class Imbalance.
IEEE Trans. Neural Networks Learn. Syst.
Xu Yang, Jiyuan Feng, Yongxin Tong, Lingzhi Wang, Songyue Guo, Binxing Fang, Qing Liao
2025 A* conf
Do Mentioned Items Truly Matter? Enhancing Conversational Recommender Systems with Causal Intervention and Large Language Models.
IJCAI
Lingzhi Wang, Xingshan Zeng, Kam-Fai Wong
2025 B conf
FedCSR: A Federated Framework for Multi-Platform Cross-Domain Sequential Recommendation with Dual Contrastive Learning.
COLING
Dongyi Zheng, Hongyu Zhang, Jianyang Zhai, Lin Zhong, Lingzhi Wang, Jiyuan Feng, Xiangke Liao, Yonghong Tian, Nong Xiao, Qing Liao
2025 B conf
FedSS: A Federated Semantic Segmentation Framework with Domain-Agnostic Feature Extraction and Fair Aggregation.
IJCNN
Liwen Liang, Jiyuan Feng, Lingzhi Wang, Qing Liao
2025 B conf
IndiTag: An Online Media Bias Analysis System Using Fine-Grained Bias Indicators.
ICPADS
Luyang Lin, Lingzhi Wang, Jinsong Guo, Jing Li, Kam-Fai Wong
2025 B conf
Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception.
COLING
Luyang Lin, Lingzhi Wang, Jinsong Guo, Kam-Fai Wong
2025 A* conf
Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models.
AAAI
Lingzhi Wang, Xingshan Zeng, Jinsong Guo, Kam-Fai Wong, Georg Gottlob
2025 J jnl
ToolACE-MT: Non-Autoregressive Generation for Agentic Multi-Turn Interaction.
CoRR
Xingshan Zeng, Weiwen Liu, Lingzhi Wang, Liangyou Li, Fei Mi, Yasheng Wang, Lifeng Shang, Xin Jiang, Qun Liu
2025 J jnl
ToolACE-R: Tool Learning with Adaptive Self-Refinement.
CoRR
Xingshan Zeng, Weiwen Liu, Xu Huang, Zezhong Wang, Lingzhi Wang, Liangyou Li, Yasheng Wang, Lifeng Shang, Xin Jiang, Ruiming Tang, Qun Liu
2024 J jnl
A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers.
ACM Comput. Surv.
Xiaoyan Zhao, Yang Deng, Min Yang, Lingzhi Wang, Rui Zhang, Hong Cheng, Wai Lam, Ying Shen, Ruifeng Xu
2024 — conf
DPDLLM: A Black-box Framework for Detecting Pre-training Data from Large Language Models.
ACL (Findings)
Baohang Zhou, Zezhong Wang, Lingzhi Wang, Hongru Wang, Ying Zhang, Kehui Song, Xuhui Sui, Kam-Fai Wong
2024 J jnl
Improving Conversational Recommender System Via Contextual and Time-Aware Modeling With Less Domain-Specific Knowledge.
IEEE Trans. Knowl. Data Eng.
Lingzhi Wang, Shafiq Joty, Wei Gao, Xingshan Zeng, Kam-Fai Wong
2024 J jnl
IndiTag: An Online Media Bias Analysis and Annotation System Using Fine-Grained Bias Indicators.
CoRR
Luyang Lin, Lingzhi Wang, Jinsong Guo, Jing Li, Kam-Fai Wong
2024 — conf
IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias Indicators.
EACL (Findings)
Luyang Lin, Lingzhi Wang, Xiaoyan Zhao, Jing Li, Kam-Fai Wong
2024 J jnl
IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias Indicators.
CoRR
Luyang Lin, Lingzhi Wang, Xiaoyan Zhao, Jing Li, Kam-Fai Wong
2024 J jnl
Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception.
CoRR
Luyang Lin, Lingzhi Wang, Jinsong Guo, Kam-Fai Wong
2024 — conf
LLM-REDIAL: A Large-Scale Dataset for Conversational Recommender Systems Created from User Behaviors with LLMs.
ACL (Findings)
Tingting Liang, Chenxin Jin, Lingzhi Wang, Wenqi Fan, Congying Xia, Kai Chen, Yuyu Yin
2024 A* conf
LLMEdgeRefine: Enhancing Text Clustering with LLM-Based Boundary Point Refinement.
EMNLP
Zijin Feng, Luyang Lin, Lingzhi Wang, Hong Cheng, Kam-Fai Wong
2024 — conf
PACAR: Automated Fact-Checking with Planning and Customized Action Reasoning Using Large Language Models.
LREC/COLING
Xiaoyan Zhao, Lingzhi Wang, Zhanghao Wang, Hong Cheng, Rui Zhang, Kam-Fai Wong
2024 J jnl
Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models.
CoRR
Lingzhi Wang, Xingshan Zeng, Jinsong Guo, Kam-Fai Wong, Georg Gottlob
2024 — conf
TPE: Towards Better Compositional Reasoning over Cognitive Tools via Multi-persona Collaboration.
NLPCC (2)
Hongru Wang, Huimin Wang, Lingzhi Wang, Minda Hu, Rui Wang, Boyang Xue, Yongfeng Huang, Kam-Fai Wong
2023 J jnl
A Comprehensive Survey on Deep Learning for Relation Extraction: Recent Advances and New Frontiers.
CoRR
Xiaoyan Zhao, Yang Deng, Min Yang, Lingzhi Wang, Rui Zhang, Hong Cheng, Wai Lam, Ying Shen, Ruifeng Xu
2023 J jnl
A Survey of the Evolution of Language Model-Based Dialogue Systems.
CoRR
Hongru Wang, Lingzhi Wang, Yiming Du, Liang Chen, Jingyan Zhou, Yufei Wang, Kam-Fai Wong
2023 J jnl
Delta-LoRA: Fine-Tuning High-Rank Parameters with the Delta of Low-Rank Matrices.
CoRR
Bojia Zi, Xianbiao Qi, Lingzhi Wang, Jianan Wang, Kam-Fai Wong, Lei Zhang
2023 — conf
KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment.
ACL (1)
Lingzhi Wang, Tong Chen, Wei Yuan, Xingshan Zeng, Kam-Fai Wong, Hongzhi Yin
2023 J jnl
KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment.
CoRR
Lingzhi Wang, Tong Chen, Wei Yuan, Xingshan Zeng, Kam-Fai Wong, Hongzhi Yin
2023 A conf
Opportunities and Challenges in Neural Dialog Tutoring.
EACL
Jakub Macina, Nico Daheim, Lingzhi Wang, Tanmay Sinha, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan
2023 J jnl
Opportunities and Challenges in Neural Dialog Tutoring.
CoRR
Jakub Macina, Nico Daheim, Lingzhi Wang, Tanmay Sinha, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan
2023 J jnl
Quotation Recommendation for Multi-party Online Conversations Based on Semantic and Topic Fusion.
ACM Trans. Inf. Syst.
Lingzhi Wang, Xingshan Zeng, Kam-Fai Wong
2023 — conf
Strategize Before Teaching: A Conversational Tutoring System with Pedagogy Self-Distillation.
EACL (Findings)
Lingzhi Wang, Mrinmaya Sachan, Xingshan Zeng, Kam-Fai Wong
2023 J jnl
Strategize Before Teaching: A Conversational Tutoring System with Pedagogy Self-Distillation.
CoRR
Lingzhi Wang, Mrinmaya Sachan, Xingshan Zeng, Kam-Fai Wong
2023 J jnl
TPE: Towards Better Compositional Reasoning over Conceptual Tools with Multi-persona Collaboration.
CoRR
Hongru Wang, Huimin Wang, Lingzhi Wang, Minda Hu, Rui Wang, Boyang Xue, Hongyuan Lu, Fei Mi, Kam-Fai Wong
2022 J jnl
Improving Conversational Recommender System via Contextual and Time-Aware Modeling with Less Domain-Specific Knowledge.
CoRR
Lingzhi Wang, Shafiq R. Joty, Wei Gao, Xingshan Zeng, Kam-Fai Wong
2022 — conf
Learning When and What to Quote: A Quotation Recommender System with Mutual Promotion of Recommendation and Generation.
EMNLP (Findings)
Lingzhi Wang, Xingshan Zeng, Kam-Fai Wong
2022 J jnl
Modeling Global and Local Interactions for Online Conversation Recommendation.
ACM Trans. Inf. Syst.
Xingshan Zeng, Jing Li, Lingzhi Wang, Kam-Fai Wong
2022 — conf
RecInDial: A Unified Framework for Conversational Recommendation with Pretrained Language Models.
AACL/IJCNLP (1)
Lingzhi Wang, Huang Hu, Lei Sha, Can Xu, Daxin Jiang, Kam-Fai Wong
2022 A* conf
Successful New-entry Prediction for Multi-Party Online Conversations via Latent Topics and Discourse Modeling.
WWW
Lingzhi Wang, Jing Li, Xingshan Zeng, Kam-Fai Wong
2021 J jnl
Continuity of Topic, Interaction, and Query: Learning to Quote in Online Conversations.
CoRR
Lingzhi Wang, Jing Li, Xingshan Zeng, Haisong Zhang, Kam-Fai Wong
2021 J jnl
Finetuning Large-Scale Pre-trained Language Models for Conversational Recommendation with Knowledge Graph.
CoRR
Lingzhi Wang, Huang Hu, Lei Sha, Can Xu, Kam-Fai Wong, Daxin Jiang
2021 — conf
Quotation Recommendation and Interpretation Based on Transformation from Queries to Quotations.
ACL/IJCNLP (2)
Lingzhi Wang, Xingshan Zeng, Kam-Fai Wong
2021 J jnl
Quotation Recommendation and Interpretation Based on Transformation from Queries to Quotations.
CoRR
Lingzhi Wang, Xingshan Zeng, Kam-Fai Wong
2021 — conf
Re-entry Prediction for Online Conversations via Self-Supervised Learning.
EMNLP (Findings)
Lingzhi Wang, Xingshan Zeng, Huang Hu, Kam-Fai Wong, Daxin Jiang
2021 J jnl
Re-entry Prediction for Online Conversations via Self-Supervised Learning.
CoRR
Lingzhi Wang, Xingshan Zeng, Huang Hu, Kam-Fai Wong, Daxin Jiang
2021 J jnl
Successful New-entry Prediction for Multi-Party Online Conversations via Latent Topics and Discourse Modeling.
CoRR
Lingzhi Wang, Jing Li, Xingshan Zeng, Kam-Fai Wong
2020 — conf
Continuity of Topic, Interaction, and Query: Learning to Quote in Online Conversations.
EMNLP (1)
Lingzhi Wang, Jing Li, Xingshan Zeng, Haisong Zhang, Kam-Fai Wong
2019 — conf
Coupling Global and Local Context for Unsupervised Aspect Extraction.
EMNLP/IJCNLP (1)
Ming Liao, Jing Li, Haisong Zhang, Lingzhi Wang, Xixin Wu, Kam-Fai Wong