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LLMs demonstrate an uncanny ability to process unstructured data, and as such, have the potential to go beyond search and run complex, semantic analyses at scale.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2021 · 2005
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Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. In NSDI
Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauly, Michael J. Franklin, Scott Shenker, and Ion Stoica. 2012 · 2012
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Microsoft COCO: Common Objects in Context. In Computer Vision – ECCV 2014 , David Fleet, Tomas Pajdla, Bernt Schiele, and Tinne Tuytelaars (Eds.). Springer International Publishing, Cham, 740–755
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Ray: A Distributed Framework for Emerging AI Applications. In OSDI
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End-to-End Object Detection with Transformers. In ECCV
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Natural language to SQL: Where are we today?
Hyeonji Kim, Byeong-Hoon So, Wook-Shin Han, and Hongrae Lee. 2020 · 2020
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Deep entity matching with pre-trained language models
Yuliang Li, Jinfeng Li, Yoshihiko Suhara, AnHai Doan, and Wang-Chiew Tan. 2020 · 2020
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Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai. 2020 · 2020
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Donut: Document understanding transformer without ocr
Geewook Kim, Teakgyu Hong, Moonbin Yim, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, and Seunghyun Park. 2021 · 2021
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Layoutlmv3: Pre-training for document ai with unified text and image masking. In Proceedings of the 30th ACM International Conference on Multimedia . 4083–4091
Yupan Huang, Tengchao Lv, Lei Cui, Yutong Lu, and Furu Wei. 2022 · 2022
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PP-OCRv3: More Attempts for the Improvement of Ultra Lightweight OCR System
Chenxia Li, Weiwei Liu, Ruoyu Guo, Xiaoting Yin, Kaitao Jiang, Yongkun Du, Yuning Du, Lingfeng Zhu, Baohua Lai, Xiaoguang Hu, Dianhai Yu, and Yanjun Ma. 2022 · 2022
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Can Foundation Models Wrangle Your Data?
Avanika Narayan, Ines Chami, Laurel Orr, and Christopher Ré. 2022 · 2022
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PubTables-1M: Towards Comprehensive Table Extraction From Unstructured Documents. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 4634–4642
Brandon Smock, Rohith Pesala, and Robin Abraham. 2022 · 2022
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Annotating columns with pre-trained language models. In Proceedings of the 2022 International Conference on Management of Data . 1493–1503
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Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes
Simran Arora, Brandon Yang, Sabri Eyuboglu, Avanika Narayan, Andrew Hojel, Immanuel Trummer, and Christopher Ré. 2023 · 2023
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ICDAR 2023 Competition on Robust Layout Segmentation in Corporate Documents. In Document Analysis and Recognition - ICDAR 2023 . Springer Nature Switzerland, 471–482
Towards Accurate and Efficient Document Analytics with Large Language Models
Yiming Lin, Madelon Hulsebos, Ruiying Ma, Shreya Shankar, Sepanta Zeigham, Aditya G. Parameswaran, and Eugene Wu. 2024 · 2024
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A Declarative System for Optimizing AI Workloads
Chunwei Liu, Matthew Russo, Michael Cafarella, Lei Cao, Peter Baille Chen, Zui Chen, Michael Franklin, Tim Kraska, Samuel Madden, and Gerardo Vitagliano. 2024a · 2024
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Azure AI Document Intelligence
Microsoft. 2024 · 2024
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LOTUS: Enabling Semantic Queries with LLMs Over Tables of Unstructured and Structured Data
Liana Patel, Siddharth Jha, Carlos Guestrin, and Matei Zaharia. 2024 · 2024
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UniTable: Towards a Unified Framework for Table Recognition via Self-Supervised Pretraining
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Christoph Auer, Ahmed Nassar, Maksym Lysak, Michele Dolfi, Nikolaos Livathinos, and Peter Staar. 2023 · 2023
Cited alongside, same era.
Lost in the Middle: How Language Models Use Long Contexts
Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2023 · 2023
Cited alongside, same era.
CAESURA: Language Models as Multi-Modal Query Planners
Matthias Urban and Carsten Binnig. 2023 · 2023
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Amazon Textract
Amazon. 2024 · 2024
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Text2SQL is Not Enough: Unifying AI and Databases with TAG
Asim Biswal, Liana Patel, Siddarth Jha, Amog Kamsetty, Shu Liu, Joseph E. Gonzalez, Carlos Guestrin, and Matei Zaharia. 2024 · 2024
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CHORUS: Foundation Models for Unified Data Discovery and Exploration
Moe Kayali, Anton Lykov, Ilias Fountalis, Nikolaos Vasiloglou, Dan Olteanu, and Dan Suciu. 2024 · 2024
Cited alongside, same era.
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Aryn. 2024a
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Aryn. 2024b
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ShengYun Peng, Aishwarya Chakravarthy, Seongmin Lee, Xiaojing Wang, Rajarajeswari Balasubramaniyan, and Duen Horng Chau. 2024 · 2024
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CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL
Mohammadreza Pourreza, Hailong Li, Ruoxi Sun, Yeounoh Chung, Shayan Talaei, Gaurav Tarlok Kakkar, Yu Gan, Amin Saberi, Fatma Ozcan, and Sercan O. Arik. 2024 · 2024
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DIN-SQL: Decomposed in-context learning of text-to-SQL with self-correction
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DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing
Shreya Shankar, Aditya G. Parameswaran, and Eugene Wu. 2024 · 2024
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Benchmarking PDF segmentation and parsing models
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Unstructured Serverless API
Unstructured. 2024 · 2024
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