12 papers
SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD
Dongfang Li, Xiaodong Luo, Ruoyu Sun +62
Full-parameter post-training of trillion-parameter-scale MoE models introduces substantial system-level challenges for large-scale distributed training, including severe memory pre…
FlowLOB: Efficient and Controllable Limit Order Book Generation with Flow Matching
Zhuohan Wang, Andreea Bacalum, Ollie Olby +2
Limit order book (LOB) simulators are most useful to practitioners when they combine realistic market dynamics, computationally efficient sampling, controllable scenario generation…
LOB-ID: Evaluating Synthetic Market Data by Inception Distances
Andreea Bacalum, Zhuohan Wang, Ollie Olby +2
Generative models of limit orderbook (LOB) data have advanced rapidly, but their evaluation often focuses on stylised facts and selected market statistics. These measures provide u…
Diffusion Models in Finance: A Survey
Zhuohan Wang, Carmine Ventre
Diffusion generative models have rapidly emerged as powerful tools for modeling complex financial data. Their appeal is both structural and practical: they offer stable likelihood-…
DINOv3 Beats Specialized Detectors: A Simple Foundation Model Baseline for Image Forensics
Jieming Yu, Qiuxiao Feng, Zhuohan Wang +1
With the rapid advancement of deep generative models, realistic fake images have become increasingly accessible, yet existing localization methods rely on complex designs and still…
DiffLOB: Diffusion Models for Counterfactual Generation in Limit Order Books
Zhuohan Wang, Carmine Ventre
Modern generative models for limit order books (LOBs) can reproduce realistic market dynamics, but remain fundamentally passive: they either model what typically happens without ac…
Alpha Discovery via Grammar-Guided Learning and Search
Han Yang, Dong Hao, Zhuohan Wang +2
Automatically discovering formulaic alpha factors is a central problem in quantitative finance. Existing methods often ignore syntactic and semantic constraints, relying on exhaust…
ORGEval: Graph-Theoretic Evaluation of LLMs in Optimization Modeling
Zhuohan Wang, Ziwei Zhu, Ziniu Li +8
Formulating optimization problems for industrial applications demands significant manual effort and domain expertise. While Large Language Models (LLMs) show promise in automating…
DiffVolume: Diffusion Models for Volume Generation in Limit Order Books
Zhuohan Wang, Carmine Ventre
Modeling limit order books (LOBs) dynamics is a fundamental problem in market microstructure research. In particular, generating high-dimensional volume snapshots with strong tempo…
A Financial Time Series Denoiser Based on Diffusion Model
Zhuohan Wang, Carmine Ventre
Financial time series often exhibit low signal-to-noise ratio, posing significant challenges for accurate data interpretation and prediction and ultimately decision making. Generat…
SBoRA: Low-Rank Adaptation with Regional Weight Updates
Lai-Man Po, Yuyang Liu, Haoxuan Wu +5
This paper introduces Standard Basis LoRA (SBoRA), a novel parameter-efficient fine-tuning approach for Large Language Models that builds upon the pioneering works of Low-Rank Adap…
Batch-Instructed Gradient for Prompt Evolution:Systematic Prompt Optimization for Enhanced Text-to-Image Synthesis
Xinrui Yang, Zhuohan Wang, Anthony Hu
Text-to-image models have shown remarkable progress in generating high-quality images from user-provided prompts. Despite this, the quality of these images varies due to the models…