VLDB 2026 Research / reviewers in the wild / expert
Shahrad Mohammadzadeh
dblp:367/5819
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
2 papers |
Language models and text generation · 59% Deep learning architectures and training · 36% Trustworthy machine learning · 5% | |
| Network and information security
1 paper |
Security and privacy of machine learning · 100% |
Topics — the 8 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Deep learning architectures and training › regularization
dropout |
0.9 | 1 | 2025 | Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025 |
Natural language and speech › Language models and text generation
hallucination detection |
0.9 | 1 | 2025 | Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025 |
Natural language and speech › Language models and text generation
hallucination mitigation |
0.9 | 1 | 2025 | Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025 |
Natural language and speech › Language models and text generation
large language model safety |
0.9 | 1 | 2025 | Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility · EMNLP 2025 |
Machine learning › Deep learning architectures and training › regularization
training regularization |
0.9 | 1 | 2025 | Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025 |
Security and privacy of machine learning › adversarial attack
jailbreak attack |
0.9 | 1 | 2025 | Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility · EMNLP 2025 |
Natural language and speech › Language models and text generation
large language model training |
0.3 | 1 | 2025 | Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model Training · ACL (1) 2025 |
Machine learning › Trustworthy machine learning
robustness |
0.3 | 1 | 2025 | Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility · EMNLP 2025 |
Methods — techniques the papers use, named apart from their topics
fine-tuning · 1.7sensitivity dropout · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Hallucination Detox: Sensitivity Dropout (SenD) for Large Language Model TrainingabstractShahrad Mohammadzadeh, Juan David Guerra, Marco Bonizzato, Reihaneh Rabbany, Golnoosh Farnadi. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025. Shahrad Mohammadzadeh, Juan David Guerra, Marco Bonizzato, Reihaneh Rabbany, Golnoosh Farnadi |
ACL (1) | 1 |
| 2025 | Jailbreak-Tuning: Models Efficiently Learn Jailbreak SusceptibilityabstractBrendan Murphy, Dillon Bowen, Shahrad Mohammadzadeh, Tom Tseng, Julius Broomfield, Adam Gleave, Kellin Pelrine. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. 2025. Brendan Murphy, Dillon Bowen, Shahrad Mohammadzadeh, Tom Tseng, Julius Broomfield, Adam Gleave, Kellin Pelrine |
EMNLP | 3 |