Wenjie Mo

Affiliations:
  • University of California, Davis, Department of Computer Science, Davis, CA, USA


According to our database1, Wenjie Mo authored at least 13 papers between 2023 and 2026.

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

2026
Triaging Threats to Specialized Guardrails.
CoRR, May, 2026

When Vision Speaks for Sound.
CoRR, May, 2026

DebugLM: Learning Traceable Training Data Provenance for LLMs.
CoRR, March, 2026

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025
OmniGuard: Unified Omni-Modal Guardrails with Deliberate Reasoning.
CoRR, December, 2025

Towards Policy-Compliant Agents: Learning Efficient Guardrails For Policy Violation Detection.
CoRR, October, 2025

Test-time Backdoor Mitigation for Black-Box Large Language Models with Defensive Demonstrations.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Rethinking Backdoor Detection Evaluation for Language Models.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

ThinkGuard: Deliberative Slow Thinking Leads to Cautious Guardrails.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Mitigating Backdoor Threats to Large Language Models: Advancement and Challenges.
Proceedings of the 60th Annual Allerton Conference on Communication, 2024

2023
Test-time Backdoor Mitigation for Black-Box Large Language Models with Defensive Demonstrations.
CoRR, 2023

A Causal View of Entity Bias in (Large) Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023


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