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Yiquan Zhang

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Artificial Intelligence Computation and Language Machine Learning Populations and Evolution

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preprint2026arXiv

BacktestBench: Benchmarking Large Language Models for Automated Quantitative Strategy Backtesting

Quantitative backtesting is essential for evaluating trading strategies but remains hampered by high technical barriers and limited scalability. While Large Language Models (LLMs) offer a transformative path to automate this complex, interdisciplinary workflow through advanced code generation, tool usage, and agentic planning, the practical realization is significantly challenged by the current lack of a large-scale benchmark dedicated to automated quantitative backtesting, which hinders progress in this field. To bridge this critical gap, we introduce BacktestBench, the first large-scale benchmark for automated quantitative backtesting. Built from over 6 million real market records, it comprises 18,246 meticulously annotated question-answering pairs across four task categories: metrics calculation, ticker selection, strategy selection, and parameter confirmation. We also propose AutoBacktest, a robust multi-agent baseline that translates natural language strategies into reproducible backtests by coordinating a Summarizer for semantic factor extraction, a Retriever for validated SQL generation, and a Coder for Python backtesting implementation. Our evaluation on 23 mainstream LLMs, complemented by targeted ablations, identifies key factors that influence end-to-end performance and highlights the importance of grounded verification and standardized indicator representations.

preprint2020arXiv

A deep Convolutional Neural Network for topology optimization with strong generalization ability

This paper proposes a deep Convolutional Neural Network(CNN) with strong generalization ability for structural topology optimization. The architecture of the neural network is made up of encoding and decoding parts, which provide down- and up-sampling operations. In addition, a popular technique, namely U-Net, was adopted to improve the performance of the proposed neural network. The input of the neural network is a well-designed tensor with each channel includes different information for the problem, and the output is the layout of the optimal structure. To train the neural network, a large dataset is generated by a conventional topology optimization approach, i.e. SIMP. The performance of the proposed method was evaluated by comparing its efficiency and accuracy with SIMP on a series of typical optimization problems. Results show that a significant reduction in computation cost was achieved with little sacrifice on the optimality of design solutions. Furthermore, the proposed method can intelligently solve problems under boundary conditions not being included in the training dataset.

preprint2014arXiv

Epidemic clones, oceanic gene pools and eco-LD in the free living marine pathogen Vibrio parahaemolyticus

We investigated global patterns of variation in 157 whole genome sequences of Vibrio parahaemolyticus, a free-living and seafood associated marine bacterium. Pandemic clones, responsible for recent outbreaks of gastroenteritis in humans have spread globally. However, there are oceanic gene pools, one located in the oceans surrounding Asia and another in the Mexican Gulf. Frequent recombination means that most isolates have acquired the genetic profile of their current location. We investigated the genetic structure in the Asian gene pool by calculating the effective population size in two different ways. Under standard neutral models, the two estimates should give similar answers but we found a thirty fold difference. We propose that this discrepancy is caused by the subdivision of the species into a hundred or more ecotypes which are maintained stably in the population. To investigate the genetic factors involved, we used 51 unrelated isolates to conduct a genome-wide scan for epistatically interacting loci. We found a single example of strong epistasis between distant genome regions. A majority of strains had a type VI secretion system associated with bacterial killing. The remaining strains had genes associated with biofilm formation and regulated by c-di-GMP signaling. All strains had one or other of the two systems and none of isolate had complete complements of both systems, although several strains had remnants. Further top-down analysis of patterns of linkage disequilibrium within frequently recombining species will allow a detailed understanding of how selection acts to structure the pattern of variation within natural bacterial populations.