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Jian Cui

8 accepted papers

2026

ChemEval: A Multi-level and Fine-grained Chemical Capability Evaluation for Large Language Models

ICLR 2026poster

The emergence of Large Language Models (LLMs) in chemistry marks a significant advancement in applying artificial intelligence to chemical sciences. While these models show promising potential, their effective application in chemistry demands sophisticated evaluation protocols that address the field…

Cited by 0SourcecodeScholar
2025

LoRO: Real-Time on-Device Secure Inference for LLMs via TEE-Based Low Rank Obfuscation

NeurIPS 2025poster

While Large Language Models (LLMs) have gained remarkable success, they are consistently at risk of being stolen when deployed on untrusted edge devices. As a solution, TEE-based secure inference has been proposed to protect valuable model property. However, we identify a statistical vulnerability i…

Cited by 0SourceScholar
2024

GI-PIP: Do We Require Impractical Auxiliary Dataset for Gradient Inversion Attacks?

ICASSP 2024accepted

Deep gradient inversion attacks expose a serious threat to Federated Learning (FL) by accurately recovering private data from shared gradients. However, the state-of-the-art heavily relies on impractical assumptions to access excessive auxiliary data, which violates the basic data partitioning princ…

Cited by 0SourceScholar
2024

Ignore Me But Don’t Replace Me: Utilizing Non-Linguistic Elements for Pretraining on the Cybersecurity Domain

NAACL 2024findings

Cybersecurity information is often technically complex and relayed through unstructured text, making automation of cyber threat intelligence highly challenging. For such text domains that involve high levels of expertise, pretraining on in-domain corpora has been a popular method for language models…

Cited by 3SourcePDFScholar
2023

DarkBERT: A Language Model for the Dark Side of the Internet

ACL 2023long

Recent research has suggested that there are clear differences in the language used in the Dark Web compared to that of the Surface Web. As studies on the Dark Web commonly require textual analysis of the domain, language models specific to the Dark Web may provide valuable insights to researchers.…

2023

Descriptive Prompt Paraphrasing for Target-Oriented Multimodal Sentiment Classification

EMNLP 2023long findings

Target-Oriented Multimodal Sentiment Classification (TMSC) aims to perform sentiment polarity on a target jointly considering its corresponding multiple modalities including text, image, and others. Current researches mainly work on either of two types of targets in a decentralized manner. One type…

Cited by 0SourceScholar
2023

Instance-wise Batch Label Restoration via Gradients in Federated Learning

ICLR 2023poster

Gradient inversion attacks have posed a serious threat to the privacy of federated learning. The attacks search for the optimal pair of input and label best matching the shared gradients and the search space of the attacks can be reduced by pre-restoring labels. Recently, label restoration technique…

2023

Multimodal Propaganda Detection Via Anti-Persuasion Prompt enhanced contrastive learning

ICASSP 2023accepted

Propaganda, commonly used in memes disinformation, can influence the thinking of the audience and increase the reach of communication. Usually logical fallacy, as a kind of popular expression of memes, aims to create a logical reasonable illusion where the conclusion cannot be drawn with the use of…

Cited by 0SourceScholar