2 citations · 4 across the 10 of their papers we have counts for
12 papers
CRAFT: An Agentic Spreadsheet Form Filling System with Template Awareness
Leyao Gu, Yingjie Xiong, Zirui Tang +5
Spreadsheet form filling requires agents to consolidate external evidence, ground values to precise cells, and preserve irregular template structure. Errors in early edits can over…
The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement
Yi Duan, Ying Liu, Zirui Tang +32
Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that improve both their capabilities and the process of future improveme…
Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies
Zirui Tang, Xuanhe Zhou, Yumou Liu +19
Workspace learning requires AI agents to identify, reason over, exploit, and update explicit and implicit dependencies among heterogeneous files in a worker's workspace, enabling t…
MinerU-Popo: Universal Post-Processing Model for Structured Document Parsing
Bangrui Xu, Ziyang Miao, Xuanhe Zhou +7
VLM-based OCR models have become the de facto choice for document parsing, as they can accurately extract page-level elements (e.g., paragraphs within individual pages) together wi…
ST-Raptor: An Agentic System for Semi-Structured Table QA
Jinxiu Qu, Zirui Tang, Hongzhang Huang +7
Semi-structured table question answering (QA) is a challenging task that requires (1) precise extraction of cell contents and positions and (2) accurate recovery of key implicit lo…
MoDora: Tree-Based Semi-Structured Document Analysis System
Bangrui Xu, Qihang Yao, Zirui Tang +8
Semi-structured documents integrate diverse interleaved data elements (e.g., tables, charts, hierarchical paragraphs) arranged in various and often irregular layouts. These documen…
Can LLMs Clean Up Your Mess? A Survey of Application-Ready Data Preparation with LLMs
Wei Zhou, Jun Zhou, Haoyu Wang +16
Data preparation aims to denoise raw datasets, uncover cross-dataset relationships, and extract valuable insights from them, which is essential for a wide range of data-centric app…
LLM/Agent-as-Data-Analyst: A Survey
Zirui Tang, Weizheng Wang, Zihang Zhou +16
Large language models (LLMs) and agent techniques have brought a fundamental shift in the functionality and development paradigm of data analysis tasks (a.k.a LLM/Agent-as-Data-Ana…
MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing
Junbo Niu, Zheng Liu, Zhuangcheng Gu +58
We introduce MinerU2.5, a 1.2B-parameter document parsing vision-language model that achieves state-of-the-art recognition accuracy while maintaining exceptional computational effi…
ST-Raptor: LLM-Powered Semi-Structured Table Question Answering
Zirui Tang, Boyu Niu, Xuanhe Zhou +6
Semi-structured tables, widely used in real-world applications (e.g., financial reports, medical records, transactional orders), often involve flexible and complex layouts (e.g., h…
A Survey of LLM DATA
Xuanhe Zhou, Junxuan He, Wei Zhou +14
The integration of large language model (LLM) and data management (DATA) is rapidly redefining both domains. In this survey, we comprehensively review the bidirectional relationshi…
FeatInsight: An Online ML Feature Management System on 4Paradigm Sage-Studio Platform
Xin Tong, Xuanhe Zhou, Bingsheng He +6
Feature management is essential for many online machine learning applications and can often become the performance bottleneck (e.g., taking up to 70% of the overall latency in sale…