45 citations · 45 across the 9 of their papers we have counts for
9 papers
Silent Sabotage: Internal State Triggered Backdoor Attacks on LLM-Powered Robotic Systems
Doniyorkhon Obidov, Shivayogi Akki, Tan Chen +1
The integration of Large Language Models (LLMs) into robotic control systems is enabling a new generation of autonomous agents capable of complex reasoning and planning. While this…
Dynamic Deep Prompt Optimization for Defending Against Jailbreak Attacks on LLMs
Doniyorkhon Obidov, Honggang Yu, Xiaolong Guo +1
Large Language Models (LLMs) demonstrate impressive capabilities across many applications but remain vulnerable to jailbreak attacks, which elicit harmful or unintended content. Wh…
CAP: A Scalable Benchmark for Evaluating Cross-Site Browser Agents with Complex Actions and Perception
Zejun Xu, Taiyi Chen, Jin Li +13
Large language models are increasingly deployed as autonomous agents that interact with the web through browsers. While recent progress has been driven by benchmarks that evaluate…
StepTrigger: Contact-State-Triggered Backdoor Attacks on VLM-Powered Legged Robots
Jiageng Zhang, Doniyorkhon Obidov, Kaichen Yang
Large language models and vision-language models are increasingly used as high-level planners in robotic systems, using task goals and sensor summaries to select navigation or mani…
LoRAScan: Detecting Backdoor Prompts in Low-Rank Adapters for Large Language Models via Down-Projection Activation Spikes
Doniyorkhon Obidov, Honggang Yu, Xiaolong Guo +1
Low-rank adaptation (LoRA) enables efficient specialization and distribution of large language models through compact adapters. However, untrusted adapters introduce a supply-chain…
Genotypic Triggers: Exposing Pharmacogenomic Blind Spots via Host-Specific Backdoors in Generative Antimicrobial Peptide Models
Doniyorkhon Obidov, Xiaolong Guo, Yonghui Li +1
Large Language Models (LLMs) have accelerated drug discovery, particularly in the automated design of antimicrobial peptides (AMPs). However, current validation pipelines for pepti…
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI
Bohan Lyu, Yucheng Yang, Siqiao Huang +25
Modern AI progress has been driven by ML methods that are generalizable across settings and scalable to larger regimes. As large language models demonstrate advanced capabilities i…
LLM4SecHW: Leveraging Domain Specific Large Language Model for Hardware Debugging
Weimin Fu, Kaichen Yang, Raj Gautam Dutta +2
This paper presents LLM4SecHW, a novel framework for hardware debugging that leverages domain specific Large Language Model (LLM). Despite the success of LLMs in automating various…
Hardware Phi-1.5B: A Large Language Model Encodes Hardware Domain Specific Knowledge
Weimin Fu, Shijie Li, Yifang Zhao +6
In the rapidly evolving semiconductor industry, where research, design, verification, and manufacturing are intricately linked, the potential of Large Language Models to revolution…