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20242026
most citedFrom Deep Learning to LLMs: A survey of AI in Quantitative Investment

2 citations · 2 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2026

RRAttention: Dynamic Block Sparse Attention via Per-Head Round-Robin Shifts for Long-Context Inference

Siran Liu, Guoxia Wang, Sa Wang +7

The quadratic complexity of attention mechanisms poses a critical bottleneck for large language models processing long contexts. While dynamic sparse attention methods offer input-…

cs.CL2026

Rethinking the Reranker: Boundary-Aware Evidence Selection for Robust Retrieval-Augmented Generation

Jiashuo Sun, Pengcheng Jiang, Saizhuo Wang +13

Retrieval-Augmented Generation (RAG) systems remain brittle under realistic retrieval noise, even when the required evidence appears in the top-K results. A key reason is that retr…

cs.CE2025

DeltaLag: Learning Dynamic Lead-Lag Patterns in Financial Markets

Wanyun Zhou, Saizhuo Wang, Mihai Cucuringu +5

The lead-lag effect, where the price movement of one asset systematically precedes that of another, has been widely observed in financial markets and conveys valuable predictive si…

q-fin.CP2025

QuantBench: Benchmarking AI Methods for Quantitative Investment

Saizhuo Wang, Hao Kong, Jiadong Guo +7

The field of artificial intelligence (AI) in quantitative investment has seen significant advancements, yet it lacks a standardized benchmark aligned with industry practices. This…

cs.CE2025

Unleashing Expert Opinion from Social Media for Stock Prediction

Wanyun Zhou, Saizhuo Wang, Xiang Li +3

While stock prediction task traditionally relies on volume-price and fundamental data to predict the return ratio or price movement trend, sentiment factors derived from social med…

q-fin.CP20252 cited

From Deep Learning to LLMs: A survey of AI in Quantitative Investment

Bokai Cao, Saizhuo Wang, Xinyi Lin +4

Quantitative investment (quant) is an emerging, technology-driven approach in asset management, increasingy shaped by advancements in artificial intelligence. Recent advances in de…