21 citations · 27 across the 9 of their papers we have counts for
10 papers
SeisMamba: Low-Latency Single-Station Seismic Magnitude Estimation for Spatially Distributed Earthquake Early Warning
Quenton Yeo, Zhaoge Bi, Linghan Huang +3
Rapid earthquake magnitude estimation is central to earthquake early warning, yet many operational systems depend on dense regional seismic networks and region-specific calibration…
ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles
Yitian Yang, Yiqun Duan, Linghan Huang +4
Large language model (LLM)-based multi-agent simulation offers a powerful testbed for studying social opinion dynamics. Yet current approaches often adopt two contrasting methods:…
Trust in One Round: Confidence Estimation for Large Language Models via Structural Signals
Pengyue Yang, Jiawen Wen, Haolin Jin +3
Large language models (LLMs) are increasingly deployed in domains where errors carry high social, scientific, or safety costs. Yet standard confidence estimators, such as token lik…
Feature-Selective Representation Misdirection for Machine Unlearning
Taozhao Chen, Linghan Huang, Kim-Kwang Raymond Choo +1
As large language models (LLMs) are increasingly adopted in safety-critical and regulated sectors, the retention of sensitive or prohibited knowledge introduces escalating risks, r…
LLMs are All You Need? Improving Fuzz Testing for MOJO with Large Language Models
Linghan Huang, Peizhou Zhao, Huaming Chen
The rapid development of large language models (LLMs) has revolutionized software testing, particularly fuzz testing, by automating the generation of diverse and effective test inp…
NSW-EPNews: A News-Augmented Benchmark for Electricity Price Forecasting with LLMs
Zhaoge Bi, Linghan Huang, Haolin Jin +2
Electricity price forecasting is a critical component of modern energy-management systems, yet existing approaches heavily rely on numerical histories and ignore contemporaneous te…
The Tower of Babel Revisited: Multilingual Jailbreak Prompts on Closed-Source Large Language Models
Linghan Huang, Haolin Jin, Zhaoge Bi +6
Large language models (LLMs) have seen widespread applications across various domains, yet remain vulnerable to adversarial prompt injections. While most existing research on jailb…
`From Prompt to Perturbation': An Adaptive Framework for Voice-Based Jailbreaks on Audio LLMs
Linghan Huang, Bo Li, Huaming Chen +1
As large language models (LLMs) are increasingly integrated into audio-based applications, growing concerns have emerged regarding their vulnerability to audio-based adversarial at…
From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future
Haolin Jin, Linghan Huang, Haipeng Cai +3
With the rise of large language models (LLMs), researchers are increasingly exploring their applications in var ious vertical domains, such as software engineering. LLMs have achie…
On the Challenges of Fuzzing Techniques via Large Language Models
Linghan Huang, Peizhou Zhao, Huaming Chen +1
In the modern era where software plays a pivotal role, software security and vulnerability analysis are essential for secure software development. Fuzzing test, as an efficient and…