12 citations · 12 across the 11 of their papers we have counts for
14 papers
Dream2Discern: Learning from Hard Latent Variants for Runtime Failure Prediction in Multi-Agent Systems
Boxuan Zhang, Jianing Zhu, jianing Zhu +2
Reliable deployment of LLM-based multi-agent systems calls for runtime auditors that predict terminal outcomes from observed execution prefixes. These auditors typically learn from…
JIVE: Jacobian-Informed Volume Expansion for Diverse Generative Sampling
Guangxun Zhang, Brian Cai, Boxuan Zhang +2
Generative models often suffer from mode collapse and limited sample diversity. While prior works attempt to mitigate this by jointly generating a batch of samples and repelling th…
MemEye: A Visual-Centric Evaluation Framework for Multimodal Agent Memory
Minghao Guo, Qingyue Jiao, Zeru Shi +14
Long-term agent memory is increasingly multimodal, yet existing evaluations rarely test whether agents preserve the visual evidence needed for later reasoning. In prior work, many…
AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems
Boxuan Zhang, Jianing Zhu, Zeru Shi +2
LLM-based multi-agent systems are increasingly deployed on long-horizon tasks, but a single decisive error is often accepted by downstream agents and cascades into trajectory-level…
Micro-Defects Expose Macro-Fakes: Detecting AI-Generated Images via Local Distributional Shifts
Boxuan Zhang, Jianing Zhu, Qifan Wang +2
Recent generative models can produce images that appear highly realistic, raising challenges in distinguishing real and AI-generated images. Yet existing detectors based on pre-tra…
Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report v1.5
Dongrui Liu, Yi Yu, Jie Zhang +18
To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, Frontier AI Risk Management Framework in Practice presents a comp…
Data Augmentation for High-Fidelity Generation of CAR-T/NK Immunological Synapse Images
Xiang Zhang, Boxuan Zhang, Alireza Naghizadeh +4
Chimeric antigen receptor (CAR)-T and NK cell immunotherapies have transformed cancer treatment, and recent studies suggest that the quality of the CAR-T/NK cell immunological syna…
What Shapes a Creative Machine Mind? Comprehensively Benchmarking Creativity in Foundation Models
Zicong He, Boxuan Zhang, Weihao Liu +2
The meteoric rise of foundation models (FMs) has expanded their capabilities far beyond conventional tasks. Creativity, long regarded as a hallmark of human intelligence and a driv…
Dive into the Agent Matrix: A Realistic Evaluation of Self-Replication Risk in LLM Agents
Boxuan Zhang, Yi Yu, Jiaxuan Guo +1
The prevalent deployment of Large Language Model agents such as OpenClaw unlocks potential in real-world applications, while amplifying safety concerns. Among these concerns, the s…
Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report
Shanghai AI Lab, :, Xiaoyang Chen +35
To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, this report presents a comprehensive assessment of their frontier…
Shakespearean Sparks: The Dance of Hallucination and Creativity in LLMs' Decoding Layers
Zicong He, Boxuan Zhang, Lu Cheng
Large language models (LLMs) are known to hallucinate, a phenomenon often linked to creativity. While previous research has primarily explored this connection through theoretical o…
CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought
Boxuan Zhang, Ruqi Zhang
Large language models (LLMs) excel in many tasks but struggle to accurately quantify uncertainty in their generated responses. This limitation makes it challenging to detect misinf…
What If the Input is Expanded in OOD Detection?
Boxuan Zhang, Jianing Zhu, Zengmao Wang +3
Out-of-distribution (OOD) detection aims to identify OOD inputs from unknown classes, which is important for the reliable deployment of machine learning models in the open world. V…
Boosting Semi-Supervised Object Detection in Remote Sensing Images With Active Teaching
Boxuan Zhang, Zengmao Wang, Bo Du
The lack of object-level annotations poses a significant challenge for object detection in remote sensing images (RSIs). To address this issue, active learning (AL) and semi-superv…