9 citations · 10 across the 15 of their papers we have counts for
8 papers · 1 filter
Knowledge-Graph-Driven Data Synthesis for Low-Resource Software Development: A HarmonyOS Case Study
Mingwei Liu, Zheng Pei, Yanlin Wang +5
In low-resource framework development (e.g., HarmonyOS), large language models (LLMs) often lack sufficient pre-training exposure, resulting in poor code generation performance. Al…
Measuring the Security of Mobile LLM Agents under Adversarial Prompts from Untrusted Third-Party Channels
Chenghao Du, Quanfeng Huang, Tingxuan Tang +3
Large Language Models (LLMs) have transformed software development, enabling AI-powered applications known as LLM-based agents that promise to automate tasks across diverse apps an…
Model Unmerging: Making Your Models Unmergeable for Secure Model Sharing
Zihao Wang, Enneng Yang, Lu Yin +2
Model merging leverages multiple finetuned expert models to construct a multi-task model with low cost, and is gaining increasing attention. However, as a growing number of finetun…
Activation-Guided Local Editing for Jailbreaking Attacks
Jiecong Wang, Haoran Li, Hao Peng +4
Jailbreaking is an essential adversarial technique for red-teaming these models to uncover and patch security flaws. However, existing jailbreak methods face significant drawbacks.…
The Illusion of Role Separation: Hidden Shortcuts in LLM Role Learning (and How to Fix Them)
Zihao Wang, Yibo Jiang, Jiahao Yu +1
Large language models (LLMs) that integrate multiple input roles (e.g., system instructions, user queries, external tool outputs) are increasingly prevalent in practice. Ensuring t…
RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection
Yiming Huang, Junyan Zhang, Zihao Wang +5
Large Language Models (LLMs) have become powerful, but hallucinations remain a vital obstacle to their trustworthy use. Previous works improved the capability of hallucination dete…
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model
Yang Shi, Jiaheng Liu, Yushuo Guan +12
Long-context video understanding in multimodal large language models (MLLMs) faces a critical challenge: balancing computational efficiency with the retention of fine-grained spati…
Does Editing Provide Evidence for Localization?
Zihao Wang, Victor Veitch
A basic aspiration for interpretability research in large language models is to "localize" semantically meaningful behaviors to particular components within the LLM. There are vari…