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Zeinab Sadat Taghavi

3 accepted papers

2025

ImpliRet: Benchmarking the Implicit Fact Retrieval Challenge

EMNLP 2025

Retrieval systems are central to many NLP pipelines, but often rely on surface-level cues such as keyword overlap and lexical semantic similarity. To evaluate retrieval beyond these shallow signals, recent benchmarks introduce reasoning-heavy queries; however, they primarily shift the burden to quer

2024

Killing It With Zero-Shot: Adversarially Robust Novelty Detection

ICASSP 2024accepted

Novelty Detection (ND) plays a crucial role in machine learning by identifying new or unseen data during model inference. This capability is especially important for the safe and reliable operation of automated systems. Despite advances in this field, existing techniques often fail to maintain their…

Cited by 0SourceScholar
2024

Scanning Trojaned Models Using Out-of-Distribution Samples

NeurIPS 2024poster

Scanning for trojan (backdoor) in deep neural networks is crucial due to their significant real-world applications. There has been an increasing focus on developing effective general trojan scanning methods across various trojan attacks. Despite advancements, there remains a shortage of methods that…