Publications (17)
The Horizon Gap: Planning, Memory, Execution, Training, and Evaluation for Long-Horizon LLM Agents
Mingguang Chen, Licheng Wang, Bo Qu
Frontier language models solve reasoning problems in a single forward pass that would have been research contributions years ago, yet fail at multi-hour tasks: losing track of earl…
InvestPhilBench: A Multi-Layer Benchmark for Evaluating Large Language Model Procedural Reasoning in Expert Investment Philosophy
Mingguang Chen, Bo Qu
Large language models are increasingly deployed as investment research assistants, yet no benchmark tests whether they can accurately reconstruct and apply the specific procedural…
Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops
Mingguang Chen, Licheng Wang, Bo Qu
AI systems increasingly participate in their own improvement: revising their outputs, adapting their own harnesses during deployment, training on data they generate, and, increasin…
Modeling of Information Diffusion on Social Networks with Applications to WeChat
Liang Liu, Bo Qu, Bin Chen +2
Traces of user activities recorded in online social networks such as the creation, viewing and forwarding/sharing of information over time open new possibilities to quantitatively…
EDFFDNet: Towards Accurate and Efficient Unsupervised Multi-Grid Image Registration
Haokai Zhu, Bo Qu, Si-Yuan Cao +4
Previous deep image registration methods that employ single homography, multi-grid homography, or thin-plate spline often struggle with real scenes containing depth disparities due…
The Accuracy of Mean-Field Approximation for Susceptible-Infected-Susceptible Epidemic Spreading
Bo Qu, Huijuan Wang
The epidemic spreading has been studied for years by applying the mean-field approach in both homogeneous case, where each node may get infected by an infected neighbor with the sa…
MuVAM: A Multi-View Attention-based Model for Medical Visual Question Answering
Haiwei Pan, Shuning He, Kejia Zhang +3
Medical Visual Question Answering (VQA) is a multi-modal challenging task widely considered by research communities of the computer vision and natural language processing. Since mo…
Deep Attributed Network Representation Learning via Attribute Enhanced Neighborhood
Cong Li, Min Shi, Bo Qu +1
Attributed network representation learning aims at learning node embeddings by integrating network structure and attribute information. It is a challenge to fully capture the micro…
CLQT: A Closed-Loop, Cost-Aware, Strategy-Consistent Benchmark for Diagnostic Evaluation of LLM Portfolio-Management Agents
Bo Qu, Mingguang Chen
LLM agents are increasingly cast as autonomous portfolio managers, and benchmarks have moved from financial question-answering to sequential trading. Yet most still rank agents by…
SIS Epidemic Spreading with Correlated Heterogeneous Infection Rates
Bo Qu, Huijuan Wang
The epidemic spreading has been widely studied when each node may get infected by an infected neighbor with the same rate. However, the infection rate between a pair of nodes is us…
SIS Epidemic Spreading with Heterogeneous Infection Rates
Bo Qu, Huijuan Wang
In this work, we aim to understand the influence of the heterogeneity of infection rates on the Susceptible-Infected-Susceptible (SIS) epidemic spreading. Employing the classic SIS…
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Shuo Cao, Nan Ma, Jiayang Li +12
The rapid advancement of educational applications, artistic creation, and AI-generated content (AIGC) technologies has substantially increased practical requirements for comprehens…
Heterogeneous Recovery Rates against SIS Epidemics in Directed Networks
Bo Qu, Alan Hanjalic, Huijuan Wang
The nodes in communication networks are possibly and most likely equipped with different recovery resources, which allow them to recover from a virus with different rates. In this…
LLM-Enhanced Self-Evolving Reinforcement Learning for Multi-Step E-Commerce Payment Fraud Risk Detection
Bo Qu, Zhurong Wang, Daisuke Yagi +4
This paper presents a novel approach to e-commerce payment fraud detection by integrating reinforcement learning (RL) with Large Language Models (LLMs). By framing transaction risk…
Multi-task CNN Behavioral Embedding Model For Transaction Fraud Detection
Bo Qu, Zhurong Wang, Minghao Gu +4
The burgeoning e-Commerce sector requires advanced solutions for the detection of transaction fraud. With an increasing risk of financial information theft and account takeovers, d…
Non-consensus opinion model on directed networks
Bo Qu, Qian Li, Shlomo Havlin +2
Dynamic social opinion models have been widely studied on undirected networks, and most of them are based on spin interaction models that produce a consensus. In reality, however,…
The Calibration Floor: Format Repair Can Masquerade as Self-Correction at Small-to-Mid Scale
Mingguang Chen, Bo Qu, Licheng Wang
Accuracy changes after language-model self-revision are usually interpreted as changes in reasoning. We show this can fail at the answer-extraction boundary, and test the failure c…