Probabilistic Alternating-Time µ-Calculus. - Fu Song; Yedi Zhang; Taolue Chen 001; Yu Tang; Zhiwu Xu 001 (AAAI, 2019)

Making Agents' Abilities Explicit. - Yedi Zhang; Fu Song; Taolue Chen 001 (IEEE Access, 2019)

BDD4BNN: A BDD-Based Quantitative Analysis Framework for Binarized Neural Networks. - Yedi Zhang; Zhe Zhao 007; Guangke Chen; Fu Song; Taolue Chen 001 (CAV (1), 2021)

QVIP: An ILP-based Formal Verification Approach for Quantized Neural Networks. - Yedi Zhang; Zhe Zhao 007; Guangke Chen; Fu Song; Min Zhang 002; Taolue Chen 001; Jun Sun 001 (ASE, 2022)

CLEVEREST: Accelerating CEGAR-based Neural Network Verification via Adversarial Attacks. - Zhe Zhao 007; Yedi Zhang; Guangke Chen; Fu Song; Taolue Chen 001; Jiaxiang Liu 001 (SAS, 2022)

QVIP: An ILP-based Formal Verification Approach for Quantized Neural Networks. - Yedi Zhang; Zhe Zhao 007; Fu Song; Min Zhang 002; Taolue Chen 001; Jun Sun 001 (CoRR, 2022)

QEBVerif: Quantization Error Bound Verification of Neural Networks. - Yedi Zhang; Fu Song; Jun Sun 001 (CAV (2), 2023)

QFA2SR: Query-Free Adversarial Transfer Attacks to Speaker Recognition Systems. - Guangke Chen; Yedi Zhang; Zhe Zhao 007; Fu Song (USENIX Security Symposium, 2023)

A Theory of Unimodal Bias in Multimodal Learning. - Yedi Zhang; Peter E. Latham; Andrew M. Saxe (CoRR, 2023)

Precise Quantitative Analysis of Binarized Neural Networks: A BDD-based Approach. - Yedi Zhang; Zhe Zhao 007; Guangke Chen; Fu Song; Taolue Chen 001 (ACM Trans. Softw. Eng. Methodol., 2023)

Compositional Verification of Efficient Masking Countermeasures against Side-Channel Attacks. - Pengfei Gao; Yedi Zhang; Fu Song; Taolue Chen 001; François-Xavier Standaert (Proc. ACM Program. Lang., 2023)

Towards Efficient Verification of Quantized Neural Networks. - Pei Huang 002; Haoze Wu 001; Yuting Yang 002; Ieva Daukantas; Min Wu; Yedi Zhang; Clark W. Barrett (AAAI, 2024)

Certified Quantization Strategy Synthesis for Neural Networks. - Yedi Zhang; Guangke Chen; Fu Song; Jun Sun 001; Jin Song Dong (FM (1), 2024)

Understanding Unimodal Bias in Multimodal Deep Linear Networks. - Yedi Zhang; Peter E. Latham; Andrew M. Saxe (ICML, 2024)

Revisiting the Conflict-Resolving Problem from a Semantic Perspective. - Jinhao Dong; Jun Sun 001; Yun Lin 001; Yedi Zhang; Murong Ma; Jin Song Dong; Dan Hao 001 (ASE, 2024)

SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition Systems. - Guangke Chen; Yedi Zhang; Fu Song (NDSS, 2024)

A Proactive and Dual Prevention Mechanism against Illegal Song Covers empowered by Singing Voice Conversion. - Guangke Chen; Yedi Zhang; Fu Song; Ting Wang 004; Xiaoning Du 001; Yang Liu 003 (CoRR, 2024)

When Are Bias-Free ReLU Networks Like Linear Networks? - Yedi Zhang; Andrew M. Saxe; Peter E. Latham (CoRR, 2024)

The Fusion of Large Language Models and Formal Methods for Trustworthy AI Agents: A Roadmap. - Yedi Zhang; Yufan Cai; Xinyue Zuo; Xiaokun Luan; Kailong Wang 001; Zhe Hou; Yifan Zhang; Zhiyuan Wei; Meng Sun 002; Jun Sun 001; Jing Sun 002; Jin Song Dong (CoRR, 2024)

SongBsAb: A Dual Prevention Approach against Singing Voice Conversion based Illegal Song Covers. - Guangke Chen; Yedi Zhang; Fu Song; Ting Wang 004; Xiaoning Du 001; Yang Liu 003 (NDSS, 2025)

Verification of Bit-Flip Attacks against Quantized Neural Networks. - Yedi Zhang; Lei Huang; Pengfei Gao; Fu Song; Jun Sun 001; Jin Song Dong (Proc. ACM Program. Lang., 2025)

When Are Bias-Free ReLU Networks Effectively Linear Networks? - Yedi Zhang; Andrew M. Saxe; Peter E. Latham (Trans. Mach. Learn. Res., 2025)

Training Dynamics of In-Context Learning in Linear Attention. - Yedi Zhang; Aaditya K. Singh; Peter E. Latham; Andrew M. Saxe (CoRR, 2025)

Whispering Under the Eaves: Protecting User Privacy Against Commercial and LLM-powered Automatic Speech Recognition Systems. - Weifei Jin; Yuxin Cao; Junjie Su; Derui Wang; Yedi Zhang; Minhui (Jason) Xue; Jie Hao 001; Jin Song Dong; Yixian Yang (CoRR, 2025)

RvLLM: LLM Runtime Verification with Domain Knowledge. - Yedi Zhang; Sun Yi Emma; Annabelle Lee Jia En; Jin Song Dong (CoRR, 2025)