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Home/Authors/Fan Chen

Fan Chen

5 indexed papers

Recent (6 mo)
5
With code
0
Influential cites
0
Benchmarked
0

Publications per year

5
26

Top categories

AI×4Crypto×2ML×1Stats ML×1Info Retrieval×1Quantum Physics×1

Frequent co-authors

Zhuofan Chen2×
Liad Erez1×
Alon Cohen1×
Tomer Koren1×
Yishay Mansour1×
Shay Moran1×

Research Timeline

2026
Backdoor Threats in Variational Quantum Circuits: Taxonomy, Attacks, and Defenses

This paper surveys the security vulnerabilities of Variational Quantum Circuits (VQCs) to backdoor attacks, detailing various attack mechanisms and analyzing current detection and defense strategies.

When Efficiency Backfires: Cascading LLMs Trigger Cascade Failure under Adversarial Attack

This paper demonstrates that LLM cascade systems, designed for efficiency, are vulnerable to targeted adversarial attacks that simultaneously degrade both performance and cost-efficiency.

DiagramRAG: A Lightweight Framework to Retrieve Scientific Diagram for Figure Generation

DiagramRAG is a lightweight retrieval-augmented framework that uses reference diagrams to guide the completion of scientific diagrams from incomplete user sketches, achieving high performance on standard benchmarks.

The Sample Complexity of Multiclass and Sparse Contextual Bandits

The paper analyzes the sample complexity of contextual bandits in the $s$-sparse setting, achieving optimal sample bounds for identifying an $\epsilon$-optimal policy.

Xetrieval: Mechanistically Explaining Dense Retrieval

Xetrieval introduces an embedding-level framework to mechanistically explain dense retrieval decisions by decomposing high-dimensional embeddings into sparse, human-interpretable features.

Highlighted terms show continued research focus across papers

Papers

cs.LGcs.AIstat.MLRecentMay 28, 2026

The Sample Complexity of Multiclass and Sparse Contextual Bandits

Liad Erez, Fan Chen, Alon Cohen, Tomer Koren +3 more

The paper analyzes the sample complexity of contextual bandits in the $s$-sparse setting, achieving optimal sample bounds for identifying an $\epsilon$-optimal policy.

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cs.AIcs.IRRecentMay 28, 2026

Xetrieval: Mechanistically Explaining Dense Retrieval

Zhixin Cai, Jun Bai, Yang Liu, Jiaqi Li +6 more

Xetrieval introduces an embedding-level framework to mechanistically explain dense retrieval decisions by decomposing high-dimensional embeddings into sparse, human-interpretable features.

View →
cs.AIRecentMay 27, 2026

DiagramRAG: A Lightweight Framework to Retrieve Scientific Diagram for Figure Generation

Xinjiang Yu, Junyi Han, Zhuofan Chen, Chi Zhang +6 more

DiagramRAG is a lightweight retrieval-augmented framework that uses reference diagrams to guide the completion of scientific diagrams from incomplete user sketches, achieving high performance on stand…

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cs.CRcs.AIRecentMay 17, 2026

When Efficiency Backfires: Cascading LLMs Trigger Cascade Failure under Adversarial Attack

Zehan Sun, Dingfan Chen, Songze Li

This paper demonstrates that LLM cascade systems, designed for efficiency, are vulnerable to targeted adversarial attacks that simultaneously degrade both performance and cost-efficiency.

View →
quant-phcs.CRRecentMay 13, 2026

Backdoor Threats in Variational Quantum Circuits: Taxonomy, Attacks, and Defenses

Lei Jiang, Fan Chen

This paper surveys the security vulnerabilities of Variational Quantum Circuits (VQCs) to backdoor attacks, detailing various attack mechanisms and analyzing current detection and defense strategies.

View →