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T01. LLM agent orchestration and harness design

External research on how multiple language-model agents are planned, routed, and evaluated.

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  1. T01-13Similar problemSince 2025

    Why Do Multi-Agent LLM Systems Fail?

    Authors
    Mert Cemri, Melissa Z. Pan, Shuyi Yang, Lakshya A. Agrawal, Bhavya Chopra, Rishabh Tiwari, Kurt Keutzer, Aditya Parameswaran, Dan Klein, Kannan Ramchandran, Matei Zaharia, Joseph E. Gonzalez, Ion Stoica
    Year
    2025
    Venue
    NeurIPS 2025 Datasets and Benchmarks Track spotlight

    Korean review of T01-13

  2. T01-19Similar problemSince 2025

    tau^2-Bench: Evaluating Conversational Agents in a Dual-Control Environment

    Authors
    Victor Barres, Honghua Dong, Soham Ray, Xujie Si, Karthik Narasimhan
    Year
    2026
    Venue
    arXiv 2025-06-09

    Korean review of T01-19

  3. T01-12Similar problemSince 2025

    tau-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

    Authors
    Shunyu Yao, Noah Shinn, Pedram Razavi, Karthik Narasimhan
    Year
    2025
    Venue
    ICLR 2025 Poster

    Korean review of T01-12

  4. T01-7Similar problem

    WebArena: A Realistic Web Environment for Building Autonomous Agents

    Authors
    Shuyan Zhou, Frank F. Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, Uri Alon, Graham Neubig
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T01-7

  5. T01-8Similar problem

    SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

    Authors
    Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, Karthik Narasimhan
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T01-8

  6. T01-16Similar problem

    AgentBench: Evaluating LLMs as Agents

    Authors
    Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, Jie Tang
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T01-16

  7. T01-17Similar problem

    GAIA: a benchmark for General AI Assistants

    Authors
    Grégoire Mialon, Clémentine Fourrier, Craig Swift, Thomas Wolf, Yann LeCun, Thomas Scialom
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T01-17

  8. T01-18Similar problem

    OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

    Authors
    Tianbao Xie, Danyang Zhang, Jixuan Chen, Xiaochuan Li, Siheng Zhao, Ruisheng Cao, Toh Jing Hua, Zhoujun Cheng, Dongchan Shin, Fangyu Lei, Yitao Liu, Yiheng Xu, Shuyan Zhou, Silvio Savarese, Caiming Xiong, Victor Zhong, Tao Yu
    Year
    2024
    Venue
    NeurIPS 2024

    Korean review of T01-18

T02. Recursive language models and long-context handling

Research on reading documents that do not fit in one context window.

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  1. T02-3Similar problem

    Walking Down the Memory Maze: Beyond Context Limit through Interactive Reading (MemWalker)

    Authors
    Howard Chen, Ramakanth Pasunuru, Jason Weston, Asli Celikyilmaz
    Year
    2023
    Venue
    arXiv

    Korean review of T02-3

  2. T02-6Similar problem

    Lost in the Middle: How Language Models Use Long Contexts

    Authors
    Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, Percy Liang
    Year
    2023
    Venue
    Transactions of the ACL (TACL)

    Korean review of T02-6

  3. T02-7Similar problem

    RULER: What's the Real Context Size of Your Long-Context Language Models?

    Authors
    Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, Shantanu Acharya, Dima Rekesh, Fei Jia, Yang Zhang, Boris Ginsburg
    Year
    2024
    Venue
    COLM 2024

    Korean review of T02-7

  4. T02-11Similar problem

    LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding

    Authors
    Yushi Bai, Xin Lv, Jiajie Zhang, Hongchang Lyu, Jiankai Tang, Zhidian Huang, Zhengxiao Du, Xiao Liu, Aohan Zeng, Lei Hou, Yuxiao Dong, Jie Tang, Juanzi Li
    Year
    2024
    Venue
    ACL 2024

    Korean review of T02-11

T03. Tool use, function calling, and the Model Context Protocol

External research and specifications for letting a model call outside tools.

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  1. T03-13Similar problemSince 2025

    Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions

    Authors
    Xinyi Hou, Yanjie Zhao, Shenao Wang, Haoyu Wang
    Year
    2026
    Venue
    ACM Transactions on Software Engineering and Methodology (TOSEM), 3796519

    Korean review of T03-13

  2. T03-12Similar problemSince 2025

    The Berkeley Function Calling Leaderboard (BFCL): From Tool Use to Agentic Evaluation of Large Language Models

    Authors
    Shishir G. Patil, Huanzhi Mao, Fanjia Yan, Charlie Cheng-Jie Ji, Vishnu Suresh, Ion Stoica, Joseph E. Gonzalez
    Year
    2025
    Venue
    ICML 2025

    Korean review of T03-12

  3. T03-9Similar problemSince 2025

    Tool Learning with Foundation Models

    Authors
    Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen, Ning Ding and 41 others in total (corresponding: Zhiyuan Liu, Maosong Sun)
    Year
    2025
    Venue
    ACM Computing Surveys vol. 57 no. 4, 101, pp. 40

    Korean review of T03-9

  4. T03-6Similar problem

    API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs

    Authors
    Minghao Li, Yingxiu Zhao, Bowen Yu, Feifan Song, Hangyu Li, Haiyang Yu, Zhoujun Li, Fei Huang, Yongbin Li
    Year
    2023
    Venue
    EMNLP 2023, 3102~pp. 3116

    Korean review of T03-6

T04. Planning, reflection, judging, and self-improving agents

Research on step-by-step reasoning, self-critique, and model-as-judge evaluation.

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  1. T04-9Similar problem

    Let's Verify Step by Step

    Authors
    Hunter Lightman, Vineet Kosaraju, Yura Burda, Harri Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, Karl Cobbe
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T04-9

  2. T04-11Similar problem

    Large Language Models Cannot Self-Correct Reasoning Yet

    Authors
    Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, Denny Zhou
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T04-11

  3. T04-16Similar problem

    CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

    Authors
    Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Nan Duan, Weizhu Chen
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T04-16

T05. Human review and approval workflows

Human-in-the-loop and approval research, including automation-induced complacency.

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  1. T05-21Similar problemSince 2025

    Human-In-the-Loop Software Development Agents (HULA)

    Authors
    Wannita Takerngsaksiri and 9 others (Atlassian, Monash University)
    Year
    2025
    Venue
    ICSE-SEIP 2025

    Korean review of T05-21

  2. T05-1Similar problem

    Ironies of Automation

    Authors
    Lisanne Bainbridge
    Year
    1983
    Venue
    Automatica vol. 19 no. 6 775-779

    Korean review of T05-1

  3. T05-2Similar problem

    The Out-of-the-Loop Performance Problem and Level of Control in Automation

    Authors
    Mica R. Endsley, Esin O. Kiris
    Year
    1995
    Venue
    Human Factors vol. 37 no. 2 381-394

    Korean review of T05-2

  4. T05-3Similar problem

    Humans and Automation: Use, Misuse, Disuse, Abuse

    Authors
    Raja Parasuraman, Victor Riley
    Year
    1997
    Venue
    Human Factors vol. 39 no. 2 230-253

    Korean review of T05-3

  5. T05-5Similar problem

    Complacency and Bias in Human Use of Automation: An Attentional Integration

    Authors
    Raja Parasuraman, Dietrich H. Manzey
    Year
    2010
    Venue
    Human Factors vol. 52 no. 3 381-410

    Korean review of T05-5

  6. T05-13Similar problem

    Trust in Automation: Designing for Appropriate Reliance

    Authors
    John D. Lee, Katrina A. See
    Year
    2004
    Venue
    Human Factors vol. 46 no. 1 50-80

    Korean review of T05-13

  7. T05-14Similar problem

    Guidelines for Human-AI Interaction

    Authors
    Saleema Amershi, Dan Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, Shamsi Iqbal, Paul N. Bennett, Kori Inkpen, Jaime Teevan, Ruth Kikin-Gil, Eric Horvitz
    Year
    2019
    Venue
    CHI 2019 (Honorable Mention)

    Korean review of T05-14

  8. T05-15Similar problem

    Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making

    Authors
    Yunfeng Zhang, Q. Vera Liao, Rachel K. E. Bellamy
    Year
    2020
    Venue
    ACM FAT* 2020

    Korean review of T05-15

  9. T05-16Similar problem

    Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance

    Authors
    Gagan Bansal, Tongshuang Wu, Joyce Zhou, Raymond Fok, Besmira Nushi, Ece Kamar, Marco Tulio Ribeiro, Daniel S. Weld
    Year
    2021
    Venue
    CHI 2021

    Korean review of T05-16

  10. T05-17Similar problem

    To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making

    Authors
    Zana Bucinca, Maja Barbara Malaya, Krzysztof Z. Gajos
    Year
    2021
    Venue
    Proceedings of the ACM on Human-Computer Interaction vol. 5 CSCW1 1-21

    Korean review of T05-17

  11. T05-18Similar problem

    The flaws of policies requiring human oversight of government algorithms

    Authors
    Ben Green
    Year
    2022
    Venue
    Computer Law & Security Review 45 105681

    Korean review of T05-18

T06. RAG, knowledge graphs, ontologies, and provenance

Retrieval-augmented generation and structured knowledge with traceable sources.

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  1. T06-14Similar problemSince 2025

    Enhancing retrieval-augmented generation for interoperable industrial knowledge representation and inference toward cognitive digital twins

    Authors
    Dachuan Shi, Jianzhang Li, Olga Meyer, Thomas Bauernhansl
    Year
    2025
    Venue
    Computers in Industry vol. 171, 2025, 104330

    Korean review of T06-14

  2. T06-2Similar problem

    Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

    Authors
    Patrick Lewis and 11 others
    Year
    2020
    Venue
    NeurIPS 2020

    Korean review of T06-2

  3. T06-4Similar problem

    Retrieval-Augmented Generation for Large Language Models: A Survey

    Authors
    Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Meng Wang, Haofen Wang
    Year
    2024
    Venue
    arXiv (v1 2023-12-18, v5 2024-03-27)

    Korean review of T06-4

  4. T06-9Similar problem

    Measuring Attribution in Natural Language Generation Models

    Authors
    Hannah Rashkin, Vitaly Nikolaev, Matthew Lamm, Lora Aroyo, Michael Collins, Dipanjan Das, Slav Petrov, Gaurav Singh Tomar, Iulia Turc, David Reitter
    Year
    2023
    Venue
    Computational Linguistics vol. 49 no. 4, 2023, pp. 777-840

    Korean review of T06-9

  5. T06-12Similar problem

    Knowledge Graphs

    Authors
    Aidan Hogan and 17 others
    Year
    2022
    Venue
    ACM Computing Surveys vol. 54 no. 4, 71, pp. 1-37

    Korean review of T06-12

  6. T06-13Similar problem

    A benchmark dataset with Knowledge Graph generation for Industry 4.0 production lines

    Authors
    Muhammad Yahya, Aabid Ali, Qaiser Mehmood, Lan Yang, John G. Breslin, Muhammad Intizar Ali
    Year
    2024
    Venue
    Semantic Web vol. 15 no. 2, 2024, pp. 461-479

    Korean review of T06-13

T07. Structured output, schema validation, and document understanding

Research on forcing machine-checkable output and reading business documents.

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  1. T07-11Similar problemSince 2025

    JSONSchemaBench: A Rigorous Benchmark of Structured Outputs for Language Models

    Authors
    Saibo Geng, Hudson Cooper, Michał Moskal, Samuel Jenkins, Julian Berman, Nathan Ranchin, Robert West, Eric Horvitz, Harsha Nori
    Year
    2025
    Venue
    arXiv

    Korean review of T07-11

  2. T07-3Similar problem

    TableFormer: Table Structure Understanding with Transformers

    Authors
    Ahmed Nassar, Nikolaos Livathinos, Maksym Lysak, Peter Staar
    Year
    2022
    Venue
    CVPR 2022

    Korean review of T07-3

  3. T07-5Similar problem

    FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

    Authors
    Guillaume Jaume, Hazim Kemal Ekenel, Jean-Philippe Thiran
    Year
    2019
    Venue
    ICDAR 2019 OST (Workshop on Open Services and Tools for Document Analysis)

    Korean review of T07-5

  4. T07-6Similar problem

    DocVQA: A Dataset for VQA on Document Images

    Authors
    Minesh Mathew, Dimosthenis Karatzas, C.V. Jawahar
    Year
    2021
    Venue
    WACV 2021

    Korean review of T07-6

  5. T07-12Similar problem

    Let Me Speak Freely? A Study On The Impact Of Format Restrictions On Large Language Model Performance

    Authors
    Zhi Rui Tam, Cheng-Kuang Wu, Yi-Lin Tsai, Chieh-Yen Lin, Hung-yi Lee, Yun-Nung Chen
    Year
    2024
    Venue
    EMNLP 2024 Industry Track

    Korean review of T07-12

  6. T07-13Similar problem

    Grammar-Aligned Decoding

    Authors
    Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick, Nadia Polikarpova, Loris D'Antoni
    Year
    2024
    Venue
    NeurIPS 2024

    Korean review of T07-13

T08. OCR, vision-language models, and industrial display reading

Research on reading meters, indicators, and shop-floor displays from images.

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  1. T08-1Similar problemSince 2025

    Do Vision-Language Models Measure Up? Benchmarking Visual Measurement Reading with MeasureBench

    Authors
    Fenfen Lin, Yesheng Liu, Haiyu Xu, Chen Yue, Zheqi He, Mingxuan Zhao, Miguel Hu Chen, Jiakang Liu, JG Yao, Xi Yang
    Year
    2026
    Venue
    arXiv (cs.CV, cs.AI)

    Korean review of T08-1

  2. T08-3Similar problem

    Convolutional Neural Networks for Automatic Meter Reading

    Authors
    Rayson Laroca, Victor Barroso, Matheus A. Diniz, Gabriel R. Goncalves, William Robson Schwartz, David Menotti
    Year
    2019
    Venue
    Journal of Electronic Imaging 28(1), 013023

    Korean review of T08-3

  3. T08-4Similar problem

    Utilizing Smartphone-Based Machine Learning in Medical Monitor Data Collection: Seven Segment Digit Recognition

    Authors
    Varun N. Shenoy, Oliver O. Aalami
    Year
    2018
    Venue
    AMIA Annual Symposium Proceedings 2017;2017:1564-1570

    Korean review of T08-4

T09. Industrial time series, anomaly detection, and predictive maintenance

Sensor-driven fault detection, remaining useful life, and condition monitoring research.

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  1. T09-1Similar problem

    Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress

    Authors
    Renjie Wu, Eamonn J. Keogh
    Year
    2023
    Venue
    IEEE Transactions on Knowledge and Data Engineering vol. 35 no. 3 pp. 2421 pp. 2429

    Korean review of T09-1

  2. T09-2Similar problem

    Towards a Rigorous Evaluation of Time-series Anomaly Detection

    Authors
    Siwon Kim, Kukjin Choi, Hyun-Soo Choi, Byunghan Lee, Sungroh Yoon
    Year
    2022
    Venue
    AAAI 2022

    Korean review of T09-2

  3. T09-3Similar problem

    The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection Benchmark

    Authors
    Qinghua Liu, John Paparrizos
    Year
    2024
    Venue
    NeurIPS 2024 Datasets and Benchmarks Track

    Korean review of T09-3

  4. T09-4Similar problem

    Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection

    Authors
    John Paparrizos, Paul Boniol, Themis Palpanas, Ruey S. Tsay, Aaron Elmore, Michael J. Franklin
    Year
    2022
    Venue
    Proceedings of the VLDB Endowment vol. 15 no. 11 pp. 2774 pp. 2787

    Korean review of T09-4

  5. T09-5Similar problem

    A Review on Outlier/Anomaly Detection in Time Series Data

    Authors
    Ane Blazquez-Garcia, Angel Conde, Usue Mori, Jose A. Lozano
    Year
    2021
    Venue
    ACM Computing Surveys vol. 54 no. 3 56, pp. 1 pp. 33

    Korean review of T09-5

  6. T09-7Similar problem

    Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding

    Authors
    Kyle Hundman, Valentino Constantinou, Christopher Laporte, Ian Colwell, Tom Soderstrom
    Year
    2018
    Venue
    KDD 2018

    Korean review of T09-7

  7. T09-9Similar problem

    A Dataset to Support Research in the Design of Secure Water Treatment Systems (SWaT)

    Authors
    Jonathan Goh, Sridhar Adepu, Khurum Nazir Junejo, Aditya Mathur
    Year
    2017
    Venue
    CRITIS 2016

    Korean review of T09-9

  8. T09-13Similar problem

    Damage Propagation Modeling for Aircraft Engine Run-to-Failure Simulation

    Authors
    Abhinav Saxena, Kai Goebel, Don Simon, Neil Eklund
    Year
    2008
    Venue
    2008 International Conference on Prognostics and Health Management (IEEE)

    Korean review of T09-13

  9. T09-14Similar problem

    A review on machinery diagnostics and prognostics implementing condition-based maintenance

    Authors
    Andrew K. S. Jardine, Daming Lin, Dragan Banjevic
    Year
    2006
    Venue
    Mechanical Systems and Signal Processing vol. 20 no. 7 pp. 1483 pp. 1510

    Korean review of T09-14

  10. T09-15Similar problem

    Machinery health prognostics: A systematic review from data acquisition to RUL prediction

    Authors
    Yaguo Lei, Naipeng Li, Liang Guo, Ningbo Li, Tao Yan, Jing Lin
    Year
    2018
    Venue
    Mechanical Systems and Signal Processing vol. 104 pp. 799 pp. 834

    Korean review of T09-15

T10. AutoML, model selection, evaluation design, and experiment tracking

Research on choosing and validating models instead of shipping a single fitted model.

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  1. T10-1Similar problem

    Random Search for Hyper-Parameter Optimization

    Authors
    James Bergstra, Yoshua Bengio
    Year
    2012
    Venue
    Journal of Machine Learning Research vol. 13 pp. 281-305

    Korean review of T10-1

  2. T10-9Similar problem

    AMLB: an AutoML Benchmark

    Authors
    Pieter Gijsbers, Marcos L. P. Bueno, Stefan Coors, Erin LeDell, Sebastien Poirier, Janek Thomas, Bernd Bischl, Joaquin Vanschoren
    Year
    2024
    Venue
    Journal of Machine Learning Research 25 101, pp. 1-65

    Korean review of T10-9

  3. T10-10Similar problem

    Statistical Comparisons of Classifiers over Multiple Data Sets

    Authors
    Janez Demsar
    Year
    2006
    Venue
    Journal of Machine Learning Research vol. 7 pp. 1-30

    Korean review of T10-10

  4. T10-11Similar problem

    On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation

    Authors
    Gavin C. Cawley, Nicola L. C. Talbot
    Year
    2079
    Venue
    Journal of Machine Learning Research vol. 11 pp. 2079-2107

    Korean review of T10-11

  5. T10-12Similar problem

    Evaluating time series forecasting models: An empirical study on performance estimation methods

    Authors
    Vitor Cerqueira, Luis Torgo, Igor Mozetic
    Year
    2028
    Venue
    Machine Learning vol. 109 pp. 1997-2028

    Korean review of T10-12

T11. Object detection, multi-object tracking, and video understanding

Detection and tracking backbones behind camera-based safety and inspection work.

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  1. T11-3.2Similar problem

    Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT)

    Authors
    Nicolai Wojke, Alex Bewley, Dietrich Paulus
    Year
    2017

    Korean review of T11-3.2

  2. T11-5.2Similar problem

    SlowFast Networks for Video Recognition

    Authors
    Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, Kaiming He
    Year
    2019

    Korean review of T11-5.2

T12. Video understanding and evidence selection with vision-language models

Research on explaining what a camera saw and pointing back to the evidence frame.

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  1. T12-13Similar problemSince 2025

    Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

    Authors
    Chaoyou Fu, Yuhan Dai, Yongdong Luo, Lei Li, Shuhuai Ren, Renrui Zhang, Zihan Wang, Chenyu Zhou, Yunhang Shen
    Year
    2025
    Venue
    CVPR 2025, pp. 24108-24118

    Korean review of T12-13

  2. T12-6Similar problem

    Can I Trust Your Answer? Visually Grounded Video Question Answering (NExT-GQA)

    Authors
    Junbin Xiao, Angela Yao, Yicong Li, Tat-Seng Chua
    Year
    2024
    Venue
    CVPR 2024 (Highlight)

    Korean review of T12-6

  3. T12-9Similar problem

    QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries (Moment-DETR)

    Authors
    Jie Lei, Tamara L. Berg, Mohit Bansal
    Year
    2021
    Venue
    NeurIPS 2021

    Korean review of T12-9

  4. T12-12Similar problem

    EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understanding

    Authors
    Karttikeya Mangalam, Raiymbek Akshulakov, Jitendra Malik
    Year
    2023
    Venue
    NeurIPS 2023, Datasets and Benchmarks Track

    Korean review of T12-12

  5. T12-14Similar problem

    Evaluating Object Hallucination in Large Vision-Language Models (POPE)

    Authors
    Yifan Li, Yifan Du, Kun Zhou, Jinpeng Wang, Wayne Xin Zhao, Ji-Rong Wen
    Year
    2023
    Venue
    EMNLP 2023

    Korean review of T12-14

  6. T12-15Similar problem

    VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models

    Authors
    Yuxuan Wang, Yueqian Wang, Dongyan Zhao, Cihang Xie, Zilong Zheng
    Year
    2024
    Venue
    arXiv

    Korean review of T12-15

T13. Edge AI, streaming inference, and resource scheduling

Running models near the machine under limited compute and latency budgets.

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  1. T13-2Similar problem

    Live Video Analytics at Scale with Approximation and Delay-Tolerance

    Authors
    Haoyu Zhang, Ganesh Ananthanarayanan, Peter Bodik, Matthai Philipose, Paramvir Bahl, Michael J. Freedman
    Year
    2017
    Venue
    USENIX NSDI 2017, pp. 377-392

    Korean review of T13-2

  2. T13-3Similar problem

    AWStream: Adaptive Wide-Area Streaming Analytics

    Authors
    Ben Zhang, Xin Jin, Sylvia Ratnasamy, John Wawrzynek, Edward A. Lee
    Year
    2018
    Venue
    ACM SIGCOMM 2018, pp. 236-252

    Korean review of T13-3

  3. T13-4Similar problem

    Chameleon: Scalable Adaptation of Video Analytics

    Authors
    Junchen Jiang, Ganesh Ananthanarayanan, Peter Bodik, Siddhartha Sen, Ion Stoica
    Year
    2018
    Venue
    ACM SIGCOMM 2018, pp. 253-266

    Korean review of T13-4

  4. T13-5Similar problem

    Reducto: On-Camera Filtering for Resource-Efficient Real-Time Video Analytics

    Authors
    Yuanqi Li, Arthi Padmanabhan, Pengzhan Zhao, Yufei Wang, Guoqing Harry Xu, Ravi Netravali
    Year
    2020
    Venue
    ACM SIGCOMM 2020, pp. 359-376

    Korean review of T13-5

  5. T13-18Similar problem

    MillWheel: Fault-Tolerant Stream Processing at Internet Scale

    Authors
    Tyler Akidau, Alex Balikov, Kaya Bekiroğlu, Slava Chernyak, Josh Haberman, Reuven Lax, Sam McVeety, Daniel Mills, Paul Nordstrom, Sam Whittle
    Year
    2013
    Venue
    Proceedings of the VLDB Endowment, Vol. 6, No. 11, 2013, pp. 1033-1044

    Korean review of T13-18

  6. T13-19Similar problem

    The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing

    Authors
    Tyler Akidau, Robert Bradshaw, Craig Chambers, Slava Chernyak, Rafael J. Fernandez-Moctezuma, Reuven Lax, Sam McVeety, Daniel Mills, Frances Perry, Eric Schmidt, Sam Whittle
    Year
    2015
    Venue
    Proceedings of the VLDB Endowment, Vol. 8, No. 12, 2015, pp. 1792-1803

    Korean review of T13-19

T14. Industrial protocol translation, code generation, and program synthesis

Research on generating and checking the code that talks to plant equipment.

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  1. T14-1Similar problem

    Evaluating Large Language Models Trained on Code

    Authors
    Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan (58 authors in total, OpenAI)
    Year
    2021

    Korean review of T14-1

  2. T14-2Similar problem

    ChatGPT for PLC/DCS Control Logic Generation

    Authors
    Heiko Koziolek, Sten Gruener, Virendra Ashiwal (ABB)
    Year
    2023
    Venue
    arXiv, pp. 8 6

    Korean review of T14-2

  3. T14-6Similar problem

    Automated Control Logic Test Case Generation using Large Language Models

    Authors
    Heiko Koziolek, Virendra Ashiwal, Soumyadip Bandyopadhyay, Chandrika K R
    Year
    2024
    Venue
    IEEE ETFA 2024 (29th IEEE International Conference on Emerging Technologies and Factory Automation), pp. 1-8

    Korean review of T14-6

  4. T14-7Similar problem

    Automated generation of OPC UA information models - A review and outlook

    Authors
    Axel Busboom
    Year
    2024
    Venue
    Journal of Industrial Information Integration (Elsevier), vol. 39, 100602

    Korean review of T14-7

  5. T14-15Similar problem

    Program Synthesis with Large Language Models

    Authors
    Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, Charles Sutton (11 authors in total, Google Research)
    Year
    2021

    Korean review of T14-15

T15. OPC UA, Asset Administration Shell, MQTT, and manufacturing interoperability

Specifications and research for describing equipment and moving its data.

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  1. T15-2.1Similar problem

    The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0

    Authors
    Martin Wollschlaeger, Thilo Sauter, Jürgen Jasperneite
    Year
    2017
    Venue
    IEEE Industrial Electronics Magazine 11(1), pp.17-27, 2017-03

    Korean review of T15-2.1

  2. T15-2.2Similar problem

    Insights into Mapping Solutions Based on OPC UA Information Model Applied to the Industry 4.0 Asset Administration Shell

    Authors
    Salvatore Cavalieri, Marco Giuseppe Salafia
    Year
    2020
    Venue
    Computers 9(2), 28, 2020

    Korean review of T15-2.2

  3. T15-2.4Similar problem

    OPC UA versus ROS, DDS, and MQTT: Performance Evaluation of Industry 4.0 Protocols

    Authors
    Stefan Profanter, Ayhun Tekat, Kirill Dorofeev, Markus Rickert, Alois Knoll
    Year
    2019
    Venue
    2019 IEEE International Conference on Industrial Technology (ICIT), pp.955-962

    Korean review of T15-2.4

  4. T15-2.9Similar problem

    Streaming Machine Generated Data via the MQTT Sparkplug B Protocol for Smart Factory Operations

    Authors
    Pavel Koprov, Ashwin Ramachandran, Yuan-Shin Lee, Paul Cohen, Binil Starly
    Year
    2022
    Venue
    Manufacturing Letters 33, pp.66-73, 2022

    Korean review of T15-2.9

T16. Manufacturing knowledge graphs and semantic layers

Research on giving plant data a shared meaning across systems.

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  1. T16-7Similar problemSince 2025

    Fault Cause Identification across Manufacturing Lines through Ontology-Guided and Process-Aware FMEA Graph Learning with LLMs

    Authors
    Sho Okazaki, Kohei Kaminishi, Takuma Fujiu, Yusheng Wang, Manu Sasidharan, Jun Ota
    Year
    2026
    Venue
    arXiv (cs.IR)

    Korean review of T16-7

  2. T16-3Similar problem

    Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review

    Authors
    Georg Buchgeher, David Gabauer, Jorge Martinez-Gil, Lisa Ehrlinger
    Year
    2021
    Venue
    IEEE Access, vol. 9, 55537~pp. 55554

    Korean review of T16-3

  3. T16-12Similar problem

    The Industry 4.0 Standards Landscape from a Semantic Integration Perspective

    Authors
    Irlan Grangel-Gonzalez, Paul Baptista, Lavdim Halilaj, Steffen Lohmann, Maria-Esther Vidal, Christian Mader, Soren Auer
    Year
    2017
    Venue
    2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 1~pp. 8

    Korean review of T16-12

T17. Natural language to SQL and grounded report generation

Research on turning a question into a checked query and a sourced report.

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  1. T17-5Similar problemSince 2025

    Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows

    Authors
    Fangyu Lei, Jixuan Chen, Yuxiao Ye, Ruisheng Cao
    Year
    2025
    Venue
    ICLR 2025 Oral

    Korean review of T17-5

  2. T17-1Similar problem

    Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

    Authors
    Victor Zhong, Caiming Xiong, Richard Socher
    Year
    2017
    Venue
    arXiv

    Korean review of T17-1

  3. T17-2Similar problem

    Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

    Authors
    Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga and 8 others
    Year
    2018
    Venue
    EMNLP 2018

    Korean review of T17-2

  4. T17-4Similar problem

    Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs

    Authors
    Jinyang Li, Binyuan Hui, Ge Qu, Jiaxi Yang
    Year
    2023
    Venue
    NeurIPS 2023

    Korean review of T17-4

  5. T17-17Similar problem

    ToTTo: A Controlled Table-To-Text Generation Dataset

    Authors
    Ankur Parikh, Xuezhi Wang, Sebastian Gehrmann, Manaal Faruqui, Bhuwan Dhingra, Diyi Yang, Dipanjan Das
    Year
    2020
    Venue
    EMNLP 2020

    Korean review of T17-17

  6. T17-18Similar problem

    QTSumm: Query-Focused Summarization over Tabular Data

    Authors
    Yilun Zhao, Zhenting Qi, Linyong Nan, Boyu Mi, Yixin Liu, Weijin Zou, Simeng Han, Ruizhe Chen, Xiangru Tang, Yumo Xu, Dragomir Radev, Arman Cohan
    Year
    2023
    Venue
    EMNLP 2023

    Korean review of T17-18

T18. AI quality management, model monitoring, and audit trails

Research and standards for keeping a deployed model accountable over time.

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  1. T18-1Similar problem

    Hidden Technical Debt in Machine Learning Systems

    Authors
    D. Sculley and 9 others (Google)
    Year
    2015
    Venue
    NeurIPS(NIPS) 28

    Korean review of T18-1

  2. T18-7Similar problem

    A Survey on Concept Drift Adaptation

    Authors
    João Gama, Indrė Žliobaitė, Albert Bifet, Mykola Pechenizkiy, Abdelhamid Bouchachia
    Year
    2014
    Venue
    ACM Computing Surveys 46(4), 1-37

    Korean review of T18-7

  3. T18-8Similar problem

    Learning under Concept Drift: A Review

    Authors
    Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang
    Year
    2019
    Venue
    IEEE Transactions on Knowledge and Data Engineering 31(12), 2346-2363

    Korean review of T18-8

  4. T18-10Similar problem

    Operationalizing Machine Learning: An Interview Study

    Authors
    Shreya Shankar, Rolando Garcia, Joseph M. Hellerstein, Aditya G. Parameswaran
    Year
    2022
    Venue
    arXiv (UC Berkeley)

    Korean review of T18-10

From research to product use

Operating capabilities, pilots, and technologies in development are identified separately.

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