This page (revision-102) was last changed on 04-Oct-2025 22:52 by 程龚

This page was created on 12-Jul-2022 12:19 by 程龚

Only authorized users are allowed to rename pages.

Only authorized users are allowed to delete pages.

Page revision history

Version Date Modified Size Author Changes ... Change note
102 04-Oct-2025 22:52 28 KB 程龚 to previous
101 04-Oct-2025 22:51 28 KB 程龚 to previous | to last

Page References

Incoming links Outgoing links

Version management

Difference between version and

At line 7 changed 6 lines
*A pair programming framework for code generation via multi-plan exploration and feedback-driven refinement. __Proc. ASE__
*Can ChatGPT solve relation extraction? An extensive assessment via design choice exploration. __Proc. NLPCC__
*DUNKS: Chunking and Summarizing Large and Heterogeneous Data for Dataset Search. __Proc. ISWC__
*Finetuning generative large language models with discrimination instructions for knowledge graph completion. __Proc. ISWC__
*Expanding the scope: Inductive knowledge graph reasoning with multi-starting progressive propagation. __Proc. ISWC__
*A Survey on Extractive Knowledge Graph Summarization: Applications, Approaches, Evaluation, and Future Directions. __Proc. IJCAI__
*GraDaSE: Graph-Based Dataset Search with Examples. __Proc. EMNLP__
*Mixture of LoRA experts for continual information extraction with LLMs. __Findings of EMNLP__
*Avoiding knowledge edit skipping in multi-hop question answering with guided decomposition. __Findings of EMNLP__
*TRAWL: External Knowledge-Enhanced Recommendation with LLM Assistance. __Proc. CIKM__
*Parameter-efficient Federated Knowledge Graph Embedding Learning and Unlearning. __Proc. ISWC__
*mmRAG: A Modular Benchmark for Retrieval-Augmented Generation over Text, Tables, and Knowledge Graphs. __Proc. ISWC__
*Are LLMs Really Knowledgeable for Knowledge Graph Completion? __Proc. ISWC__
At line 15 added 9 lines
!2025
*Xiang Huang, Jiayu Shen, Shanshan Huang, Sitao Cheng, Xiaxia Wang, Yuzhong Qu: TARGA: Targeted Synthetic Data Generation for Practical Reasoning over Structured Data. __Proc. ACL__
*Rongzhi Zhu, Xiangyu Liu, Zequn Sun, Yiwei Wang, Wei Hu: Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering. __Proc. ACL__
*Xiang Huang, Ting-En Lin, Feiteng Fang, Yuchuan Wu, Hangyu Li, Yuzhong Qu, Fei Huang, Yongbin Li: Reverse Preference Optimization for Complex Instruction Following. __Findings of ACL__
*Xiao Zhou, Qiaosheng Chen, Jiageng Chen, Gong Cheng: μDS: Multi-Objective Data Snippet Extraction for Dataset Search. __Proc. SIGIR__
*Qiaosheng Chen, Kaijia Huang, Xiao Zhou, Weiqing Luo, Yuanning Cui, Gong Cheng: Benchmarking Recommendation, Classification, and Tracing Based on Hugging Face Knowledge Grap. __Proc. SIGIR__
*Xiangrong Zhu, Yuexiang Xie, Yi Liu, Yaliang Li, Wei Hu: Knowledge Graph-Guided Retrieval Augmented Generation. __Proc. NAACL__
*Xiangyu Liu, Yi Liu, Silei Chen, Wei Hu: Controllable Protein Sequence Generation with LLM Preference Optimization. __Proc. AAAI__
At line 25 added 7 lines
*Yuanning Cui, Zequn Sun, Wei Hu: A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning. __Proc. NeurIPS__
*Zixian Huang, Wenhao Zhu, Gong Cheng, Lei Li, Fei Yuan: MindMerger: Efficiently Boosting LLM Reasoning in non-English Languages. __Proc. NeurIPS__
*Qiaosheng Chen, Xiao Zhou, Zhiyang Zhang, Gong Cheng: DUNKS: Chunking and Summarizing Large and Heterogeneous Data for Dataset Search. __Proc. ISWC__
*Yang Liu, Xiaobin Tian, Zequn Sun, Wei Hu: Finetuning Generative Large Language Models with Discrimination Instructions for Knowledge Graph Completion. __Proc. ISWC__
*Zhoutian Shao, Yuanning Cui, Wei Hu: Expanding the Scope: Inductive Knowledge Graph Reasoning with Multi-starting Progressive Propagation. __Proc. ISWC__
*Xinyi Wang, Wenzheng Zhao, Xiangrong Zhu, Wei Hu: Can ChatGPT Solve Relation Extraction? An Extensive Assessment via Design Choice Exploration. __Proc. NLPCC__
*Huan Zhang, Wei Cheng, Yuhan Wu, Wei Hu: A Pair Programming Framework for Code Generation via Multi-Plan Exploration and Feedback-Driven Refinement. __Proc. ASE %%(color:red;)(杰出论文奖)%%__
At line 36 added one line
*Xiaxia Wang, Gong Cheng: A Survey on Extractive Knowledge Graph Summarization: Applications, Approaches, Evaluation, and Future Directions. __Proc. IJCAI__
At line 161 changed one line
*Targeted Training for Numerical Reasoning with Large Language Models. __Knowl. Inf. Syst.__
*Continual document-level relation extraction with partial labeling compensation. __Front. Comput. Sci.__
*Evidence selection via multi-aspect query diversification for cross-document relation extraction. __Int. J. Intell. Inf. Technol.__
*Transfer-and-fusion: Integrated link prediction across knowledge graphs. __IEEE Trans. Knowl. Data Eng.__
At line 183 added 5 lines
!2025
*Yang Liu, Xiaoxia Jiang, Yuanning Cui, Yu Wang, Wei Hu: Missing data recovery for heterogeneous graphs with incremental multi-source data fusion. __Front. Comput. Sci.__
*Xiao Li, Sichen Liu, Yin Zhu, Gong Cheng: Targeted training for numerical reasoning with large language models. __Knowl. Inf. Syst.__
*Zixian Huang, Xinwei Huang, Ao Wu, Xiaxia Wang, Gong Cheng: Transforming decoder-only models into encoder-only models with improved understanding capabilities. __Knowl. Based Syst.__
At line 200 changed one line
*Liang Zheng, Yuzhong Qu, Xinqi Qian, Gong Cheng: A hierarchical co-clustering approach for entity exploration over Linked Data. __Knowl. Based Syst.__
*Liang Zheng, Yuzhong Qu, Xinqi Qian, Gong Cheng: A hierarchical co-clustering approach for entity exploration over Linked Data. __Knowl.-Based Syst.__