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From the 1 of 38 linked papers with an AI index.

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20242026
most citedAnnoRetrieve: Efficient Structured Retrieval for Unstructured Document Analysis

1 citations · 2 across the 13 of their papers we have counts for

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cs.CL2026

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,…

cs.CL2026

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…

cs.CL2026

nvBench 2.0: Resolving Ambiguity in Text-to-Visualization through Stepwise Reasoning

Tianqi Luo, Chuhan Huang, Leixian Shen +5

Text-to-Visualization (Text2VIS) enables users to create visualizations from natural language queries, making data insights more accessible. However, Text2VIS faces challenges in i…

cs.CL2025

InteractComp: Evaluating Search Agents With Ambiguous Queries

Mingyi Deng, Lijun Huang, Yani Fan +23

Language agents have demonstrated remarkable potential in web search and information retrieval. However, many search-agent benchmarks assume that user queries are complete and unam…

cs.CL2025

DataPuzzle: Breaking Free from the Hallucinated Promise of LLMs in Data Analysis

Zhengxuan Zhang, Zhuowen Liang, Yin Wu +3

Large language models (LLMs) are increasingly applied to multi-modal data analysis -- not necessarily because they offer the most precise answers, but because they provide fluent,…

cs.CL2025

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding

Bingheng Wu, Jingze Shi, Yifan Wu +2

Transformers exhibit proficiency in capturing long-range dependencies, whereas State Space Models (SSMs) facilitate linear-time sequence modeling. Notwithstanding their synergistic…