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cs.CL2025

Solver-Independent Automated Problem Formulation via LLMs for High-Cost Simulation-Driven Design

Yuchen Li, Handing Wang, Bing Xue +2

In the high-cost simulation-driven design domain, translating ambiguous design requirements into a mathematical optimization formulation is a bottleneck for optimizing product perf…

cs.LG2025

Enhancing the Effectiveness and Durability of Backdoor Attacks in Federated Learning through Maximizing Task Distinction

Zhaoxin Wang, Handing Wang, Cong Tian +1

Federated learning allows multiple participants to collaboratively train a central model without sharing their private data. However, this distributed nature also exposes new attac…

cs.LG2025

Implicit Jailbreak Attacks via Cross-Modal Information Concealment on Vision-Language Models

Zhaoxin Wang, Handing Wang, Cong Tian +1

Multimodal large language models (MLLMs) enable powerful cross-modal reasoning capabilities. However, the expanded input space introduces new attack surfaces. Previous jailbreak at…

cs.CR2025

Decoding One Safety Trigger Token for Balancing Safety and Usability in Large Language Models

Haoran Gu, Handing Wang, Yi Mei +2

Large Language Models (LLMs) have been extensively used across diverse domains, including virtual assistants, automated code generation, and scientific research. However, they rema…

cs.LG2025

ParetoHqD: Fast Offline Multiobjective Alignment of Large Language Models using Pareto High-quality Data

Haoran Gu, Handing Wang, Yi Mei +2

Aligning large language models with multiple human expectations and values is crucial for ensuring that they adequately serve a variety of user needs. To this end, offline multiobj…

cs.CV2025

Token-Level Constraint Boundary Search for Jailbreaking Text-to-Image Models

Jiangtao Liu, Zhaoxin Wang, Handing Wang +2

Text-to-Image (T2I) generation has advanced rapidly in recent years, but they also raise safety concerns due to the potential production of harmful content. In the practical deploy…