22 citations · 37 across the 28 of their papers we have counts for
8 papers · 1 filter
Automata-Based Steering of Large Language Models for Diverse Structured Generation
Xiaokun Luan, Zeming Wei, Yihao Zhang +1
Large language models (LLMs) are increasingly tasked with generating structured outputs. While structured generation methods ensure validity, they often lack output diversity, a cr…
Stabilizing Multi-Attack Adversarial Training via Bandit Optimization
Rui Wang, Zeming Wei, Xiyue Zhang +1
Deep Neural Networks (DNNs) remain vulnerable to diverse adversarial perturbations, motivating multi-attack adversarial training (AT) for improved robustness. However, existing met…
Revisiting Hallucination Detection with Effective Rank-based Uncertainty
Rui Wang, Zeming Wei, Guanzhang Yue +1
Detecting hallucinations in large language models (LLMs) remains a fundamental challenge for their trustworthy deployment. Going beyond basic uncertainty-driven hallucination detec…
Securing Multi-Agent Systems Against Corruptions via Node Contribution Backpropagation
Chengcan Wu, Zhixin Zhang, Mingqian Xu +2
Multi-Agent Systems (MAS) have become a prevalent paradigm for Large Language Model (LLM) applications. However, the complex multi-agent design in MAS introduces unique trustworthi…
Dynamic Orthogonal Continual Fine-tuning for Mitigating Catastrophic Forgettings
Zhixin Zhang, Zeming Wei, Meng Sun
Catastrophic forgetting remains a critical challenge in continual learning for large language models (LLMs), where models struggle to retain performance on historical tasks when fi…
ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction
Zeming Wei, Chengcan Wu, Meng Sun
Large Language Models (LLMs) have achieved tremendous success in various tasks, yet concerns about their safety and security have emerged. In particular, they pose risks of generat…
Secure LLM Fine-Tuning via Safety-Aware Probing
Chengcan Wu, Zhixin Zhang, Zeming Wei +3
Large language models (LLMs) have achieved remarkable success across many applications, but their ability to generate harmful content raises serious safety concerns. Although safet…
3DAffordSplat: Efficient Affordance Reasoning with 3D Gaussians
Zeming Wei, Junyi Lin, Yang Liu +4
3D affordance reasoning is essential in associating human instructions with the functional regions of 3D objects, facilitating precise, task-oriented manipulations in embodied AI.…