1 citations · 1 across the 14 of their papers we have counts for
16 papers
Deformations of Holomorphic -Contact Structures
Dan Popovici
We investigate the notion of holomorphic -contact structure, that we introduced recently in the scalar case with H. Kasuya and L. Ugarte and in the line-bundle case with K. Brod…
SearchJev: A Calibrated System-1 Model for Search Agents
Congfeng Cao, Lipeng Zuo, Konstantinos Papakostas +7
Search agents repeatedly make short decisions about relevance, evidence sufficiency, and search actions. Using generative language models for these decisions introduces latency and…
Beyond Outcome Gaps: Process-Aware Fairness Diagnosis for LLM-based Multi-Agent Decision Systems
Yiran Zhao, Lu Zhou, Liming Fang +4
LLM-based multi-agent systems (MAS) are increasingly considered for high-stakes decision-making, yet outcome-based fairness audits can miss where risks arise within the decision tr…
LLM-based Agents for Forecasting and Prediction: Methods, Training, Evaluation, and Applications
Xiaogang Xu, Jiaqi Tang, Jianmin Chen +12
Large language models (LLMs) now support forecasting systems that combine language-based reasoning with temporal data, evidence retrieval, external tools, and iterative prediction.…
EvoIdeator: Evolving Scientific Ideas through Checklist-Grounded Reinforcement Learning
Andreas Sauter, Yuyue Zhao, Jacopo Urbani +5
Scientific idea generation is a cornerstone of autonomous knowledge discovery, yet the iterative evolution required to transform initial concepts into high-quality research proposa…
From Thinker to Society: Security in Hierarchical Autonomy Evolution of AI Agents
Xiaolei Zhang, Lu Zhou, Xiaogang Xu +5
Artificial Intelligence (AI) agents have evolved from passive predictive tools into active entities capable of autonomous decision-making and environmental interaction, driven by t…
EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery
Yougang Lyu, Xi Zhang, Xinhao Yi +11
The increasing adoption of Large Language Models (LLMs) has enabled AI scientists to perform complex end-to-end scientific discovery tasks requiring coordination of specialized rol…
Fair in Mind, Fair in Action? A Synchronous Benchmark for Understanding and Generation in UMLLMs
Yiran Zhao, Lu Zhou, Xiaogang Xu +3
As artificial intelligence (AI) is increasingly deployed across domains, ensuring fairness has become a core challenge. However, the field faces a "Tower of Babel'' dilemma: fairne…
KUDA: Knowledge Unlearning by Deviating Representation for Large Language Models
Ce Fang, Zhikun Zhang, Min Chen +4
Large language models (LLMs) acquire a large amount of knowledge through pre-training on vast and diverse corpora. While this endows LLMs with strong capabilities in generation and…
Jailbreaking Commercial Black-Box LLMs with Explicitly Harmful Prompts
Chiyu Zhang, Lu Zhou, Xiaogang Xu +3
Existing black-box jailbreak attacks achieve certain success on non-reasoning models but degrade significantly on recent SOTA reasoning models. To improve attack ability, inspired…
Huawei Cloud Model-as-a-Service on the CloudMatrix384 SuperPod
Ao Xiao, Bangzheng He, Baoquan Zhang +125
Scaled-out MoE LLMs and scaled-up SuperPods create new systems challenges for production Model-as-a-Service (MaaS), requiring disaggregation, low-latency communication, and decentr…
Improving Adversarial Transferability on Vision Transformers via Forward Propagation Refinement
Yuchen Ren, Zhengyu Zhao, Chenhao Lin +4
Vision Transformers (ViTs) have been widely applied in various computer vision and vision-language tasks. To gain insights into their robustness in practical scenarios, transferabl…
Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path
Yuchen Ren, Zhengyu Zhao, Chenhao Lin +4
Transferable adversarial examples are known to cause threats in practical, black-box attack scenarios. A notable approach to improving transferability is using integrated gradients…
Adversarial Attacks of Vision Tasks in the Past 10 Years: A Survey
Chiyu Zhang, Lu Zhou, Xiaogang Xu +2
With the advent of Large Vision-Language Models (LVLMs), new attack vectors, such as cognitive bias, prompt injection, and jailbreaking, have emerged. Understanding these attacks p…
SSL-OTA: Unveiling Backdoor Threats in Self-Supervised Learning for Object Detection
Qiannan Wang, Changchun Yin, Lu Zhou +1
The extensive adoption of Self-supervised learning(SSL) has led to an increased security threat from backdoor attacks. While existing research has mainly focused on backdoor attack…
Sparse Federated Training of Object Detection in the Internet of Vehicles
Luping Rao, Chuan Ma, Ming Ding +3
As an essential component part of the Intelligent Transportation System (ITS), the Internet of Vehicles (IoV) plays a vital role in alleviating traffic issues. Object detection is…