Zekun Wu

According to our database, Zekun Wu authored at least 29 papers between 2023 and 2026.

Collaborative distances:

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

2026

AgentDrift: Unsafe Recommendation Drift Under Tool Corruption Hidden by Ranking Metrics in LLM Agents.

Zekun Wu, Adriano S. Koshiyama, Sahan Bulathwela, María Pérez-Ortiz

CoRR, March, 2026

Control Reinforcement Learning: Interpretable Token-Level Steering of LLMs via Sparse Autoencoder Features.

Seonglae Cho, Zekun Wu, Adriano S. Koshiyama

CoRR, February, 2026

The Confidence Manifold: Geometric Structure of Correctness Representations in Language Models.

Seonglae Cho, Zekun Wu, Kleyton da Costa, Adriano S. Koshiyama

CoRR, February, 2026

AgentGraph: Trace-to-Graph Platform for Interactive Analysis and Robustness Testing in Agentic AI Systems.

Zekun Wu, Seonglae Cho, Cristian E. Muñoz Villalobos, Theo King, Umar Mohammed, Emre Kazim, María Pérez-Ortiz, Sahan Bulathwela, Adriano S. Koshiyama

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

AgentSeer: Visualizing and Evaluating Temporal Actions in Agentic AI Systems.

Ilham Wicaksono, Zekun Wu, Rahul Patel, Theo King, Adriano S. Koshiyama, Philip Colin Treleaven

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

NormCode: A Semi-Formal Language for Auditable AI Planning.

Xin Guan, Yunshan Li, Zekun Wu, Ruibo Zhang

CoRR, December, 2025

Mind the Gap: Comparing Model- vs Agentic-Level Red Teaming with Action-Graph Observability on GPT-OSS-20B.

Ilham Wicaksono, Zekun Wu, Rahul Patel, Theo King, Adriano S. Koshiyama, Philip C. Treleaven

CoRR, September, 2025

Mind the Gap: Evaluating Model- and Agentic-Level Vulnerabilities in LLMs with Action Graphs.

Ilham Wicaksono, Zekun Wu, Rahul Patel, Theo King, Adriano S. Koshiyama, Philip C. Treleaven

CoRR, September, 2025

Knowledge Collapse in LLMs: When Fluency Survives but Facts Fail under Recursive Synthetic Training.

Figarri Keisha, Zekun Wu, Ze Wang, Adriano S. Koshiyama, Philip C. Treleaven

CoRR, September, 2025

Personality as a Probe for LLM Evaluation: Method Trade-offs and Downstream Effects.

Gunmay Handa, Zekun Wu, Adriano S. Koshiyama, Philip C. Treleaven

CoRR, September, 2025

CorrSteer: Steering Improves Task Performance and Safety in LLMs through Correlation-based Sparse Autoencoder Feature Selection.

Seonglae Cho, Zekun Wu, Adriano S. Koshiyama

CoRR, August, 2025

HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications.

Rishi Kalra, Zekun Wu, Ayesha Gulley, Airlie Hilliard, Xin Guan, Adriano S. Koshiyama, Philip C. Treleaven

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs.

Navya Jain, Zekun Wu, Cristian E. Muñoz Villalobos, Airlie Hilliard, Xin Guan, Adriano S. Koshiyama, Emre Kazim, Philip C. Treleaven

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

Bias Amplification: Large Language Models as Increasingly Biased Media.

Ze Wang, Zekun Wu, Yichi Zhang, Xin Guan, Navya Jain, Qinyang Lu, Saloni Gupta, Adriano S. Koshiyama

Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025

HEARTS: A Holistic Framework for Explainable, Sustainable and Robust Text Stereotype Detection.

Theo King, Zekun Wu, Adriano S. Koshiyama, Emre Kazim, Philip C. Treleaven

Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025

MPF: Aligning and Debiasing Language Models post Deployment via Multi-Perspective Fusion.

Xin Guan, PeiHsin Lin, Zekun Wu, Ze Wang, Ruibo Zhang, Emre Kazim, Adriano S. Koshiyama

Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025

CauSkelNet: Causal Representation Learning for Human Behaviour Analysis.

Xingrui Gu, Chuyi Jiang, Erte Wang, Zekun Wu, Qiang Cui, Leimin Tian, Lianlong Wu, Siyang Song, Chuang Yu

Proceedings of the 19th IEEE International Conference on Automatic Face and Gesture Recognition, 2025

SAGED: A Holistic Bias-Benchmarking Pipeline for Language Models with Customisable Fairness Calibration.

Xin Guan, Nathaniel Demchak, Saloni Gupta, Ze Wang, Ediz Ertekin Jr., Adriano S. Koshiyama, Emre Kazim, Zekun Wu

Proceedings of the 31st International Conference on Computational Linguistics, 2025

LibVulnWatch: A Deep Assessment Agent System and Leaderboard for Uncovering Hidden Vulnerabilities in Open-Source AI Libraries.

Zekun Wu, Seonglae Cho, Umar Mohammed, Cristian E. Muñoz Villalobos, Kleyton da Costa, Xin Guan, Theo King, Ze Wang, Emre Kazim, Adriano S. Koshiyama

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), 2025

2024

Bias Amplification: Language Models as Increasingly Biased Media.

Ze Wang, Zekun Wu, Jeremy Zhang, Navya Jain, Xin Guan, Adriano S. Koshiyama

CoRR, 2024

Assessing Bias in Metric Models for LLM Open-Ended Generation Bias Benchmarks.

Nathaniel Demchak, Xin Guan, Zekun Wu, Ziyi Xu, Adriano S. Koshiyama, Emre Kazim

CoRR, 2024

THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models.

Mengfei Liang, Archish Arun, Zekun Wu, Cristian E. Muñoz, Jonathan Lutch, Emre Kazim, Adriano S. Koshiyama, Philip C. Treleaven

CoRR, 2024

From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs.

Navya Jain, Zekun Wu, Cristian E. Muñoz, Airlie Hilliard, Adriano S. Koshiyama, Emre Kazim, Philip C. Treleaven

CoRR, 2024

Auditing Large Language Models for Enhanced Text-Based Stereotype Detection and Probing-Based Bias Evaluation.

Zekun Wu, Sahan Bulathwela, María Pérez-Ortiz, Adriano Soares Koshiyama

CoRR, 2024

Advancing Multimodal Data Fusion in Pain Recognition: A Strategy Leveraging Statistical Correlation and Human-Centered Perspectives.

Xingrui Gu, Zhixuan Wang, Irisa Jin, Zekun Wu

CoRR, 2024

Eliciting Personality Traits in Large Language Models.

Airlie Hilliard, Cristian E. Muñoz, Zekun Wu, Adriano Soares Koshiyama

CoRR, 2024

JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models.

Ze Wang, Zekun Wu, Xin Guan, Michael Thaler, Adriano S. Koshiyama, Skylar Lu, Sachin Beepath, Ediz Ertekin Jr., María Pérez-Ortiz

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Advancing Pain Recognition Through Statistical Correlation-Driven Multimodal Fusion.

Xingrui Gu, Zhixuan Wang, Irisa Jin, Zekun Wu

Proceedings of the 12th International Conference on Affective Computing and Intelligent Interaction, 2024

2023

Towards Auditing Large Language Models: Improving Text-based Stereotype Detection.

Zekun Wu, Sahan Bulathwela, Adriano Soares Koshiyama

CoRR, 2023