1 citations · 1 across the 5 of their papers we have counts for
7 papers
ParanoiaEval: Benchmarking Unnecessary Defensive Work in Agentic Coding
Hanjun Luo, Xiucheng Zhang, Zhuoning Xu +4
As coding agents increasingly undertake real-world work autonomously, judging whether their risk treatments are warranted has become important. Existing work evaluates related agen…
MasDrift: Benchmarking Authorization Preservation Across Multi-Agent Architectures
Zhuoning Xu, Xiucheng Zhang, Hanjun Luo +3
Multi-agent systems (MAS) decompose long-horizon tasks across supervisors and subagents, but delegated goals do not necessarily carry their original authorization boundaries. Exist…
CentaurEval: Benchmarking Human-in-the-Loop Value in Agentic Coding
Hanjun Luo, Chiming Ni, Jiaheng Wen +9
LLM-powered coding agents are reshaping the development paradigm. However, existing evaluation systems, neither traditional tests for humans nor benchmarks for LLMs, fail to captur…
T2IBias: Uncovering Societal Bias Encoded in the Latent Space of Text-to-Image Generative Models
Abu Sufian, Cosimo Distante, Marco Leo +1
Text-to-image (T2I) generative models are largely used in AI-powered real-world applications and value creation. However, their strategic deployment raises critical concerns for re…
CCD-Bench: Probing Cultural Conflict in Large Language Model Decision-Making
Hasibur Rahman, Hanan Salam
Although large language models (LLMs) are increasingly implicated in interpersonal and societal decision-making, their ability to navigate explicit conflicts between legitimately d…
On the Stability of the Jacobian Matrix in Deep Neural Networks
Benjamin Dadoun, Soufiane Hayou, Hanan Salam +2
Deep neural networks are known to suffer from exploding or vanishing gradients as depth increases, a phenomenon closely tied to the spectral behavior of the input-output Jacobian.…
AgentAuditor: Human-Level Safety and Security Evaluation for LLM Agents
Hanjun Luo, Shenyu Dai, Chiming Ni +5
Despite the rapid advancement of LLM-based agents, the reliable evaluation of their safety and security remains a significant challenge. Existing rule-based or LLM-based evaluators…