28 citations · 56 across the 36 of their papers we have counts for
15 papers · 1 filter
DocPilot: Interactive Agent Orchestration and Training for Long Visual Document Understanding
Zhuowen Liang, Xiaotian Lin, Yuyu Luo +2
Multimodal long-document question answering requires models to seek sparse evidence across pages and modalities, understand heterogeneous document content, and reason over the coll…
Can Agentic Trading Systems Pay for Their Own Intelligence?
Qiqi Duan, Changlun Li, Chen Wang +10
Large language model (LLM) agents are increasingly used in trading systems, where model reasoning, tool use, and continual decisions incur costs that are expected to produce tradin…
EidosDoc: Implicit Structure Encoding for Cost-Effective Semi-Structured Document QA
Teng Lin, Yuyu Luo, Nan Tang
Semi-structured documents are ubiquitous in scientific reports, financial statements, and technical manuals. Question answering over such documents requires simultaneous understand…
Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents
Teng Lin, Yuyu Luo, Nan Tang
Unstructured documents constitute the majority of enterprise and web data. With the rapid development of large language models(LLMs), researchers have started to build data systems…
Beyond Tables: Doc2DB-Bench for Relationally Faithful Document-to-Database Construction
Zhuowen Liang, Zhengxuan Zhang, Jiayang Wang +2
Practical AI systems increasingly need to turn long, heterogeneous documents into queryable relational databases, not isolated spreadsheets. In domains such as finance, healthcare,…
Monte Carlo Tree Search for Table-to-Multimodal Report Generation
Teng Lin, Zhiyang Zhang, Yuyu Luo +1
Automatically generating professional multimodal reports comprising both textual analysis and visual charts from structured tabular data is a critical challenge in data intelligenc…
EVOQUANT: Self-Evolving Verifier-Guided Strategy Optimization for Robust Quantitative Trading
Jie Mao, Changlun Li, Xiang Li +6
Quantitative strategy optimization remains largely manual, requiring domain experts to identify weak signals, tune risk-control rules, and repeatedly validate iterative revisions.…
CSTrader: A Testbed for Language-Grounded Trading in a Community-Driven Virtual Asset Market
Yao Shi, Kingfung Luo, Nan Tang +1
Niche asset markets, such as Counter-Strike 2 (CS2) weapon skins, are small, volatile, and heavily driven by community discussions and platform rules. These properties make them ha…
TuneAhead: Predicting Fine-tuning Performance Before Full Training Begins
Yuxiang Luo, Haonan Long, Chen Wang +6
Fine-tuning large language models (LLMs) is compute-intensive and error-prone: model performance depends sensitively on data quality and hyperparameter choices, and naïve runs can…
A Risk Decomposition Framework for Pre-Hoc Fine-Tuning Prediction
Yuxiang Luo, Chen Wang, Nan Tang
The high cost of fine-tuning LLMs poses a significant economic barrier; pre-hoc performance prediction offers a critical solution to substantially reduce this expense. However, the…
TABQAWORLD: Optimizing Multimodal Reasoning for Multi-Turn Table Question Answering
Tung Sum Thomas Kwok, Xinyu Wang, Xiaofeng Lin +7
Multimodal reasoning has emerged as a powerful framework for enhancing reasoning capabilities of reasoning models. While multi-turn table reasoning methods have improved reasoning…
Decoding Ancient Oracle Bone Script via Generative Dictionary Retrieval
Yin Wu, Gangjian Zhang, Jiayu Chen +4
Understanding humanity's earliest writing systems is crucial for reconstructing civilization's origins, yet many ancient scripts remain undeciphered. Oracle Bone Script (OBS) from…
AnnoRetrieve: Efficient Structured Retrieval for Unstructured Document Analysis
Teng Lin, Yuyu Luo, Nan Tang
Unstructured documents dominate enterprise and web data, but their lack of explicit organization hinders precise information retrieval. Current mainstream retrieval methods, especi…
Long-Document QA with Chain-of-Structured-Thought and Fine-Tuned SLMs
Zhuowen Liang, Xiaotian Lin, Zhengxuan Zhang +3
Large language models (LLMs) are widely applied to data analytics over documents, yet direct reasoning over long, noisy documents remains brittle and error-prone. Hence, we study d…
DocSage: An Information Structuring Agent for Multi-Doc Multi-Entity Question Answering
Teng Lin, Yizhang Zhu, Zhengxuan Zhang +2
Multi-document Multi-entity Question Answering inherently demands models to track implicit logic between multiple entities across scattered documents. However, existing Large Langu…