1 citations · 2 across the 9 of their papers we have counts for
9 papers
ClueWeaver: Reward-Guided Dual-Agent Evidence Reasoning for Compact LLMs on Literary Long Narratives
Jihao Zhu, Zhiwei Yang, Wenxiao Zhang +7
Humanities and social science research requires close reading of long narrative materials such as novels, scripts, archives, and case reports, yet many users have limited access to…
CARE: Pre-Execution Command Verification for Shell-Executing LLM Agents
Yu Liu, Wenxiao Zhang, Zhiwei Yang +7
Large Language Model (LLM) agents are increasingly used for coding and terminal automation, making shell-command dispatch a high-stakes runtime control point. We study command-leve…
When the Same Musical Knowledge Forgets Differently: A Clean Probe of Pathway-Dependent Forgetting
Yu Liu, Zhiwei Yang, Wenxiao Zhang +8
A model can learn that the piano piece Für Elise is calm and reflective by listening to the audio or by reading a text description, but does it matter which route that knowledge to…
Does Faithfulness-Guided Alignment Hurt Accuracy? Unlocking Accurate and Faithful Post-Retrieval Reasoning
Yu Liu, Wenxiao Zhang, Diandian Guo +6
Retrieval-augmented generation (RAG) can achieve strong answer accuracy on multi-hop questions, but outcome-level rewards often leave reasoning traces weakly grounded and difficult…
Enhancing Reliability in LLM-Integrated Robotic Systems: A Unified Approach to Security and Safety
Wenxiao Zhang, Xiangrui Kong, Conan Dewitt +2
Integrating large language models (LLMs) into robotic systems has revolutionised embodied artificial intelligence, enabling advanced decision-making and adaptability. However, ensu…
KFinEval-Pilot: A Comprehensive Benchmark Suite for Korean Financial Language Understanding
Bokwang Hwang, Seonkyu Lim, Taewoong Kim +24
We introduce KFinEval-Pilot, a benchmark suite specifically designed to evaluate large language models (LLMs) in the Korean financial domain. Addressing the limitations of existing…
A Study on Prompt Injection Attack Against LLM-Integrated Mobile Robotic Systems
Wenxiao Zhang, Xiangrui Kong, Conan Dewitt +2
The integration of Large Language Models (LLMs) like GPT-4o into robotic systems represents a significant advancement in embodied artificial intelligence. These models can process…
SafeEmbodAI: a Safety Framework for Mobile Robots in Embodied AI Systems
Wenxiao Zhang, Xiangrui Kong, Thomas Braunl +1
Embodied AI systems, including AI-powered robots that autonomously interact with the physical world, stand to be significantly advanced by Large Language Models (LLMs), which enabl…
Embodied AI in Mobile Robots: Coverage Path Planning with Large Language Models
Xiangrui Kong, Wenxiao Zhang, Jin Hong +1
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in understanding and solving mathematical problems, leading to advancements in various field…