Qing Li

Orcid: 0000-0002-6442-5003

Affiliations:
  • University of Stavanger, Department of Energy and Petroleum Engineering, Stavanger, Norway


According to our database1, Qing Li authored at least 17 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval.
CoRR, June, 2025

A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models.
CoRR, March, 2025

Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update.
CoRR, January, 2025

A Message from the Chairs.
Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

HD-NDEs: Neural Differential Equations for Hallucination Detection in LLMs.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Improved Gradient Inversion Attacks and Defenses in Federated Learning.
IEEE Trans. Big Data, December, 2024

Enhance Hyperbolic Representation Learning via Second-order Pooling.
CoRR, 2024

PoLLMgraph: Unraveling Hallucinations in Large Language Models via State Transition Dynamics.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Towards Trustworthy Dataset Distillation: A Benchmark of Privacy, Fairness and Robustness.
Proceedings of the International Joint Conference on Neural Networks, 2024

Reference-free Hallucination Detection for Large Vision-Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023
A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness.
CoRR, 2023

Learning Parameterized ODEs From Data.
IEEE Access, 2023

Solving Nonlinear Conservation Laws of Partial Differential Equations Using Graph Neural Networks.
Proceedings of the 2023 Northern Lights Deep Learning Workshop, 2023

2022
Learning the nonlinear flux function of a hidden scalar conservation law from data.
Networks Heterog. Media, 2022

2021
Towards General Deep Leakage in Federated Learning.
CoRR, 2021


  Loading...