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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. T01-1Structural parallel

    ReAct: Synergizing Reasoning and Acting in Language Models

    Authors
    Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, Yuan Cao
    Year
    2023
    Venue
    ICLR 2023

    Korean review of T01-1

  2. T01-2Structural parallel

    Toolformer: Language Models Can Teach Themselves to Use Tools

    Authors
    Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom
    Year
    2023
    Venue
    NeurIPS 2023

    Korean review of T01-2

  3. T01-3Structural parallel

    HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face

    Authors
    Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, Yueting Zhuang
    Year
    2023
    Venue
    NeurIPS 2023

    Korean review of T01-3

  4. T01-9Structural parallel

    AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversations

    Authors
    Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Jiale Liu, Ahmed Hassan Awadallah, Ryen W. White, Doug Burger, Chi Wang
    Year
    2024
    Venue
    COLM 2024

    Korean review of T01-9

  5. T01-10Structural parallel

    MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

    Authors
    Sirui Hong, Mingchen Zhuge, Jiaqi Chen, Xiawu Zheng, Yuheng Cheng, Ceyao Zhang, Jinlin Wang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, Liyang Zhou, Chenyu Ran, Lingfeng Xiao, Chenglin Wu, Jürgen Schmidhuber
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T01-10

  6. T01-11Structural parallel

    SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering

    Authors
    John Yang, Carlos E. Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, Ofir Press
    Year
    2024
    Venue
    NeurIPS 2024

    Korean review of T01-11

  7. T01-15Structural parallel

    Tree of Thoughts: Deliberate Problem Solving with Large Language Models

    Authors
    Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L. Griffiths, Yuan Cao, Karthik Narasimhan
    Year
    2023
    Venue
    NeurIPS 2023

    Korean review of T01-15

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. T02-1Structural parallelSince 2025

    Recursive Language Models

    Authors
    Alex L. Zhang, Tim Kraska, Omar Khattab
    Year
    2026
    Venue
    arXiv (MIT CSAIL)

    Korean review of T02-1

  2. T02-2Structural parallel

    RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

    Authors
    Parth Sarthi, Salman Abdullah, Aditi Tuli, Shubh Khanna, Anna Goldie, Christopher D. Manning
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T02-2

  3. T02-5Structural parallel

    Chain of Agents: Large Language Models Collaborating on Long-Context Tasks

    Authors
    Yusen Zhang, Ruoxi Sun, Yanfei Chen, Tomas Pfister, Rui Zhang, Sercan O. Arik
    Year
    2024
    Venue
    NeurIPS 2024

    Korean review of T02-5

  4. T02-9Structural parallel

    Recursively Summarizing Books with Human Feedback

    Authors
    Jeff Wu, Long Ouyang, Daniel M. Ziegler, Nisan Stiennon, Ryan Lowe, Jan Leike, Paul Christiano
    Year
    2021
    Venue
    arXiv (OpenAI)

    Korean review of T02-9

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. T03-1Structural parallel

    WebGPT: Browser-assisted question-answering with human feedback

    Authors
    Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, John Schulman
    Year
    2022

    Korean review of T03-1

  2. T03-2Structural parallel

    MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning

    Authors
    Ehud Karpas, Omri Abend, Yonatan Belinkov, Barak Lenz, Opher Lieber, Nir Ratner, Yoav Shoham, Hofit Bata, Yoav Levine, Kevin Leyton-Brown, Dor Muhlgay, Noam Rozen, Erez Schwartz, Gal Shachaf, Shai Shalev-Shwartz, Amnon Shashua, Moshe Tenenholtz
    Year
    2022

    Korean review of T03-2

  3. T03-7Structural parallel

    Gorilla: Large Language Model Connected with Massive APIs

    Authors
    Shishir G. Patil, Tianjun Zhang, Xin Wang, Joseph E. Gonzalez
    Year
    2024
    Venue
    NeurIPS 2024

    Korean review of T03-7

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. T04-1Structural parallel

    Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

    Authors
    Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, Denny Zhou
    Year
    2022
    Venue
    NeurIPS 2022

    Korean review of T04-1

  2. T04-4Structural parallel

    Self-Refine: Iterative Refinement with Self-Feedback

    Authors
    Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark
    Year
    2023
    Venue
    NeurIPS 2023

    Korean review of T04-4

  3. T04-7Structural parallel

    Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

    Authors
    Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica
    Year
    2023
    Venue
    NeurIPS 2023 Datasets and Benchmarks Track

    Korean review of T04-7

  4. T04-15Structural parallel

    Constitutional AI: Harmlessness from AI Feedback

    Authors
    Yuntao Bai, Saurav Kadavath, Sandipan Kundu and others, 51 authors in total (Anthropic)
    Year
    2022
    Venue
    arXiv

    Korean review of T04-15

T05. Human review and approval workflows

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

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  1. T05-4Structural parallel

    A Model for Types and Levels of Human Interaction with Automation

    Authors
    Raja Parasuraman, Thomas B. Sheridan, Christopher D. Wickens
    Year
    2000
    Venue
    IEEE Transactions on Systems, Man, and Cybernetics Part A vol. 30 no. 3 286-297

    Korean review of T05-4

  2. T05-6Structural parallel

    On Optimum Recognition Error and Reject Tradeoff

    Authors
    C. K. Chow
    Year
    1970
    Venue
    IEEE Transactions on Information Theory vol. 16 no. 1 41-46

    Korean review of T05-6

  3. T05-7Structural parallel

    Learning with Rejection

    Authors
    Corinna Cortes, Giulia DeSalvo, Mehryar Mohri
    Year
    2016
    Venue
    Algorithmic Learning Theory (ALT) 2016, Springer LNCS 67-82

    Korean review of T05-7

  4. T05-8Structural parallel

    Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer

    Authors
    David Madras, Toniann Pitassi, Richard Zemel
    Year
    2018
    Venue
    NeurIPS 2018

    Korean review of T05-8

  5. T05-9Structural parallel

    SelectiveNet: A Deep Neural Network with an Integrated Reject Option

    Authors
    Yonatan Geifman, Ran El-Yaniv
    Year
    2019
    Venue
    ICML 2019

    Korean review of T05-9

  6. T05-10Structural parallel

    Consistent Estimators for Learning to Defer to an Expert

    Authors
    Hussein Mozannar, David Sontag
    Year
    2020
    Venue
    ICML 2020

    Korean review of T05-10

  7. T05-11Structural parallel

    Learning to Complement Humans

    Authors
    Bryan Wilder, Eric Horvitz, Ece Kamar
    Year
    2020
    Venue
    IJCAI 2020

    Korean review of T05-11

  8. T05-12Structural parallel

    Machine Learning with a Reject Option: A survey

    Authors
    Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis
    Year
    2024
    Venue
    Machine Learning (Springer) 113 3073-3110

    Korean review of T05-12

  9. T05-19Structural parallel

    Identifying the Risks of LM Agents with an LM-Emulated Sandbox (ToolEmu)

    Authors
    Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T05-19

  10. T05-20Structural parallel

    AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents

    Authors
    Edoardo Debenedetti, Jie Zhang, Mislav Balunovic, Luca Beurer-Kellner, Marc Fischer, Florian Tramer
    Year
    2024
    Venue
    NeurIPS 2024 Datasets and Benchmarks

    Korean review of T05-20

T06. RAG, knowledge graphs, ontologies, and provenance

Retrieval-augmented generation and structured knowledge with traceable sources.

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  1. T06-1Structural parallel

    Dense Passage Retrieval for Open-Domain Question Answering

    Authors
    Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, Wen-tau Yih
    Year
    2020
    Venue
    EMNLP 2020, pp. 6769-6781

    Korean review of T06-1

  2. T06-3Structural parallel

    Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

    Authors
    Gautier Izacard, Edouard Grave
    Year
    2021
    Venue
    EACL 2021, pp. 874-880

    Korean review of T06-3

  3. T06-5Structural parallel

    From Local to Global: A Graph RAG Approach to Query-Focused Summarization

    Authors
    Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, Dasha Metropolitansky, Robert Osazuwa Ness, Jonathan Larson
    Year
    2025
    Venue
    arXiv, Microsoft Research (v1 2024-04-24, v2 2025-02-19)

    Korean review of T06-5

  4. T06-7Structural parallel

    Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

    Authors
    Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, Hannaneh Hajishirzi
    Year
    2024
    Venue
    ICLR 2024

    Korean review of T06-7

  5. T06-8Structural parallel

    Enabling Large Language Models to Generate Text with Citations

    Authors
    Tianyu Gao, Howard Yen, Jiatong Yu, Danqi Chen
    Year
    2023
    Venue
    EMNLP 2023, pp. 6465-6488

    Korean review of T06-8

  6. T06-10Structural parallel

    Provenance Semirings

    Authors
    Todd J. Green, Grigoris Karvounarakis, Val Tannen
    Year
    2007
    Venue
    PODS 2007 (ACM SIGMOD-SIGACT-SIGART Principles of Database Systems), pp. 31-40

    Korean review of T06-10

  7. T06-11Structural parallel

    Provenance in Databases: Why, How, and Where

    Authors
    James Cheney, Laura Chiticariu, Wang-Chiew Tan
    Year
    2009
    Venue
    Foundations and Trends in Databases vol. 1 no. 4, 2009, pp. 379-474

    Korean review of T06-11

T07. Structured output, schema validation, and document understanding

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

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  1. T07-10Structural parallelSince 2025

    XGrammar: Flexible and Efficient Structured Generation Engine for Large Language Models

    Authors
    Yixin Dong, Charlie F. Ruan, Yaxing Cai, Ruihang Lai, Ziyi Xu, Yilong Zhao, Tianqi Chen
    Year
    2025
    Venue
    MLSys 2025

    Korean review of T07-10

  2. T07-1Structural parallel

    LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking

    Authors
    Yupan Huang, Tengchao Lv, Lei Cui, Yutong Lu, Furu Wei
    Year
    2022
    Venue
    ACM Multimedia 2022 (ACM MM)

    Korean review of T07-1

  3. T07-2Structural parallel

    OCR-free Document Understanding Transformer

    Authors
    Geewook Kim, Teakgyu Hong, Moonbin Yim, Jeongyeon Nam, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, Seunghyun Park
    Year
    2022
    Venue
    ECCV 2022

    Korean review of T07-2

  4. T07-7Structural parallel

    PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models

    Authors
    Torsten Scholak, Nathan Schucher, Dzmitry Bahdanau
    Year
    2021
    Venue
    EMNLP 2021

    Korean review of T07-7

  5. T07-8Structural parallel

    Grammar-Constrained Decoding for Structured NLP Tasks without Finetuning

    Authors
    Saibo Geng, Martin Josifoski, Maxime Peyrard, Robert West
    Year
    2023
    Venue
    EMNLP 2023

    Korean review of T07-8

  6. T07-9Structural parallel

    Efficient Guided Generation for Large Language Models

    Authors
    Brandon T. Willard, Rémi Louf
    Year
    2023
    Venue
    arXiv, Outlines

    Korean review of T07-9

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. T08-2Structural parallelSince 2025

    DialBench: Towards Accurate Reading Recognition of Pointer Meter using Large Foundation Models

    Authors
    Futian Wang, Chaoliu Weng, Xiao Wang, Zhen Chen, Zhicheng Zhao, Jin Tang
    Year
    2025
    Venue
    arXiv (cs.CV, cs.AI)

    Korean review of T08-2

  2. T08-5Structural parallel

    An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

    Authors
    Baoguang Shi, Xiang Bai, Cong Yao
    Year
    2017
    Venue
    IEEE Transactions on Pattern Analysis and Machine Intelligence 39(11), 2298-2304 (2017)

    Korean review of T08-5

  3. T08-6Structural parallel

    Real-time Scene Text Detection with Differentiable Binarization

    Authors
    Minghui Liao, Zhaoyi Wan, Cong Yao, Kai Chen, Xiang Bai
    Year
    2020
    Venue
    AAAI 2020

    Korean review of T08-6

  4. T08-9Structural parallel

    General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model

    Authors
    Haoran Wei, Chenglong Liu, Jinyue Chen, Jia Wang, Lingyu Kong, Yanming Xu, Zheng Ge, Liang Zhao, Jianjian Sun, Yuang Peng, Chunrui Han, Xiangyu Zhang
    Year
    2024
    Venue
    arXiv (cs.CV)

    Korean review of T08-9

  5. T08-12Structural parallel

    ScreenAI: A Vision-Language Model for UI and Infographics Understanding

    Authors
    Gilles Baechler, Srinivas Sunkara, Maria Wang, Fedir Zubach, Hassan Mansoor, Vincent Etter, Victor Carbune, Jason Lin, Jindong Chen, Abhanshu Sharma
    Year
    2024
    Venue
    IJCAI 2024

    Korean review of T08-12

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. T09-6Structural parallel

    Anomaly Detection in Time Series: A Comprehensive Evaluation

    Authors
    Sebastian Schmidl, Phillip Wenig, Thorsten Papenbrock
    Year
    2022
    Venue
    Proceedings of the VLDB Endowment vol. 15 no. 9 pp. 1779 pp. 1797

    Korean review of T09-6

  2. T09-8Structural parallel

    Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network (OmniAnomaly)

    Authors
    Ya Su, Youjian Zhao, Chenhao Niu, Rong Liu, Wei Sun, Dan Pei
    Year
    2019
    Venue
    KDD 2019

    Korean review of T09-8

  3. T09-10Structural parallel

    Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

    Authors
    Jiehui Xu, Haixu Wu, Jianmin Wang, Mingsheng Long
    Year
    2022
    Venue
    ICLR 2022 (Spotlight)

    Korean review of T09-10

  4. T09-11Structural parallel

    TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

    Authors
    Shreshth Tuli, Giuliano Casale, Nicholas R. Jennings
    Year
    2022
    Venue
    Proceedings of the VLDB Endowment vol. 15 no. 6 pp. 1201 pp. 1214

    Korean review of T09-11

  5. T09-12Structural parallel

    Time-Series Anomaly Detection Service at Microsoft

    Authors
    Hansheng Ren, Bixiong Xu, Yujing Wang, Chao Yi, Congrui Huang, Xiaoyu Kou, Tony Xing, Mao Yang, Jie Tong, Qi Zhang
    Year
    2019
    Venue
    KDD 2019

    Korean review of T09-12

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. T10-2Structural parallel

    Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms

    Authors
    Chris Thornton, Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown
    Year
    2013
    Venue
    KDD 2013 (Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining) pp. 847-855

    Korean review of T10-2

  2. T10-3Structural parallel

    Efficient and Robust Automated Machine Learning (auto-sklearn)

    Authors
    Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum, Frank Hutter
    Year
    2015
    Venue
    NIPS 2015 (Advances in Neural Information Processing Systems 28)

    Korean review of T10-3

  3. T10-7Structural parallel

    AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

    Authors
    Nick Erickson, Jonas Mueller, Alexander Shirkov, Hang Zhang, Pedro Larroy, Mu Li, Alexander Smola
    Year
    2020
    Venue
    arXiv

    Korean review of T10-7

  4. T10-8Structural parallel

    Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning

    Authors
    Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer, Frank Hutter
    Year
    2022
    Venue
    Journal of Machine Learning Research 23 261

    Korean review of T10-8

  5. T10-13Structural parallel

    OpenML: Networked Science in Machine Learning

    Authors
    Joaquin Vanschoren, Jan N. van Rijn, Bernd Bischl, Luis Torgo
    Year
    2014
    Venue
    ACM SIGKDD Explorations Newsletter vol. 15 no. 2 pp. 49-60

    Korean review of T10-13

  6. T10-14Structural parallel

    Developments in MLflow: A System to Accelerate the Machine Learning Lifecycle

    Authors
    Andrew Chen, Andy Chow, Aaron Davidson, Arjun DCunha, Ali Ghodsi, Sue Ann Hong, Andy Konwinski, Clemens Mewald, Siddharth Murching, Tomas Nykodym, Paul Ogilvie, Mani Parkhe, Avesh Singh, Fen Xie, Matei Zaharia, Richard Zang, Juntai Zheng, Corey Zumar
    Year
    2020
    Venue
    DEEM 2020

    Korean review of T10-14

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. T11-1.1Structural parallel

    An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (ViT)

    Authors
    Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov and 9 others (12 authors in total)
    Year
    2021

    Korean review of T11-1.1

  2. T11-2.1Structural parallel

    Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

    Authors
    Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun
    Year
    2017

    Korean review of T11-2.1

  3. T11-2.2Structural parallel

    You Only Look Once: Unified, Real-Time Object Detection (YOLO)

    Authors
    Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi
    Year
    2016

    Korean review of T11-2.2

  4. T11-2.3Structural parallel

    Focal Loss for Dense Object Detection (RetinaNet)

    Authors
    Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, Piotr Dollar
    Year
    2017

    Korean review of T11-2.3

  5. T11-2.4Structural parallel

    End-to-End Object Detection with Transformers (DETR)

    Authors
    Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko
    Year
    2020

    Korean review of T11-2.4

  6. T11-2.5Structural parallel

    Deformable DETR: Deformable Transformers for End-to-End Object Detection

    Authors
    Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai
    Year
    2021

    Korean review of T11-2.5

  7. T11-2.6Structural parallel

    DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

    Authors
    Hao Zhang, Feng Li, Shilong Liu, Lei Zhang, Hang Su, Jun Zhu, Lionel M. Ni, Heung-Yeung Shum
    Year
    2023

    Korean review of T11-2.6

  8. T11-3.1Structural parallel

    Simple Online and Realtime Tracking (SORT)

    Authors
    Alex Bewley, Zongyuan Ge, Lionel Ott, Fabio Ramos, Ben Upcroft
    Year
    2016

    Korean review of T11-3.1

  9. T11-3.3Structural parallel

    ByteTrack: Multi-Object Tracking by Associating Every Detection Box

    Authors
    Yifu Zhang, Peize Sun, Yi Jiang, Dongdong Yu, Fucheng Weng, Zehuan Yuan, Ping Luo, Wenyu Liu, Xinggang Wang
    Year
    2022

    Korean review of T11-3.3

  10. T11-4.1Structural parallel

    Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics (MOTA, MOTP)

    Authors
    Keni Bernardin, Rainer Stiefelhagen
    Year
    2008

    Korean review of T11-4.1

  11. T11-4.2Structural parallel

    Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking (IDF1)

    Authors
    Ergys Ristani, Francesco Solera, Roger S. Zou, Rita Cucchiara, Carlo Tomasi
    Year
    2016

    Korean review of T11-4.2

  12. T11-4.3Structural parallel

    HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking

    Authors
    Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip Torr, Andreas Geiger, Laura Leal-Taixe, Bastian Leibe
    Year
    2021

    Korean review of T11-4.3

  13. T11-4.4Structural parallel

    MOT16: A Benchmark for Multi-Object Tracking

    Authors
    Anton Milan, Laura Leal-Taixe, Ian Reid, Stefan Roth, Konrad Schindler
    Year
    2016

    Korean review of T11-4.4

  14. T11-5.1Structural parallel

    Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset (I3D)

    Authors
    Joao Carreira, Andrew Zisserman
    Year
    2017

    Korean review of T11-5.1

  15. T11-6.1Structural parallel

    Learning Transferable Visual Models From Natural Language Supervision (CLIP)

    Authors
    Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh and 7 others
    Year
    2021

    Korean review of T11-6.1

  16. T11-6.2Structural parallel

    Segment Anything (SAM)

    Authors
    Alexander Kirillov, Eric Mintun, Nikhila Ravi and 9 others (12 authors in total, Meta AI Research)
    Year
    2023

    Korean review of T11-6.2

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. T12-2Structural parallelSince 2025

    Adaptive Keyframe Sampling for Long Video Understanding

    Authors
    Xi Tang, Jihao Qiu, Lingxi Xie, Yunjie Tian, Jianbin Jiao, Qixiang Ye
    Year
    2025
    Venue
    CVPR 2025

    Korean review of T12-2

  2. T12-1Structural parallelSince 2025

    Frame-Voyager: Learning to Query Frames for Video Large Language Models

    Authors
    Sicheng Yu, Chengkai Jin, Huanyu Wang, Zhenghao Chen, Sheng Jin, Zhongrong Zuo, Xiaolei Xu, Zhenbang Sun, Bingni Zhang, Jiawei Wu, Hao Zhang, Qianru Sun
    Year
    2025
    Venue
    ICLR 2025

    Korean review of T12-1

  3. T12-3Structural parallel

    Self-Chained Image-Language Model for Video Localization and Question Answering (SeViLA)

    Authors
    Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal
    Year
    2023
    Venue
    NeurIPS 2023

    Korean review of T12-3

  4. T12-4Structural parallel

    VideoAgent: Long-form Video Understanding with Large Language Model as Agent

    Authors
    Xiaohan Wang, Yuhui Zhang, Orr Zohar, Serena Yeung-Levy
    Year
    2024
    Venue
    ECCV 2024. Computer Vision - ECCV 2024, LNCS, pp. 58-76

    Korean review of T12-4

  5. T12-7Structural parallel

    TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding

    Authors
    Shuhuai Ren, Linli Yao, Shicheng Li, Xu Sun, Lu Hou
    Year
    2024
    Venue
    CVPR 2024

    Korean review of T12-7

  6. T12-8Structural parallel

    VTimeLLM: Empower LLM to Grasp Video Moments

    Authors
    Bin Huang, Xin Wang, Hong Chen, Zihan Song, Wenwu Zhu
    Year
    2024
    Venue
    CVPR 2024, pp. 14271-14280

    Korean review of T12-8

  7. T12-11Structural parallel

    BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

    Authors
    Junnan Li, Dongxu Li, Silvio Savarese, Steven Hoi
    Year
    2023
    Venue
    ICML 2023. PMLR vol. 202 pp. 19730-19742

    Korean review of T12-11

T13. Edge AI, streaming inference, and resource scheduling

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

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  1. T13-1Structural parallel

    Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge

    Authors
    Yiping Kang, Johann Hauswald, Cao Gao, Austin Rovinski, Trevor Mudge, Jason Mars, Lingjia Tang
    Year
    2017
    Venue
    ASPLOS 2017, pp. 615-629

    Korean review of T13-1

  2. T13-6Structural parallel

    Ekya: Continuous Learning of Video Analytics Models on Edge Compute Servers

    Authors
    Romil Bhardwaj, Zhengxu Xia, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Nikolaos Karianakis, Kevin Hsieh, Paramvir Bahl, Ion Stoica
    Year
    2022
    Venue
    USENIX NSDI 2022, pp. 119-135

    Korean review of T13-6

  3. T13-7Structural parallel

    Clipper: A Low-Latency Online Prediction Serving System

    Authors
    Daniel Crankshaw, Xin Wang, Giulio Zhou, Michael J. Franklin, Joseph E. Gonzalez, Ion Stoica
    Year
    2017
    Venue
    USENIX NSDI 2017, pp. 613-627

    Korean review of T13-7

  4. T13-8Structural parallel

    Serving DNNs like Clockwork: Performance Predictability from the Bottom Up

    Authors
    Arpan Gujarati, Reza Karimi, Safya Alzayat, Wei Hao, Antoine Kaufmann, Ymir Vigfusson, Jonathan Mace
    Year
    2020
    Venue
    USENIX OSDI 2020, pp. 443-462

    Korean review of T13-8

  5. T13-17Structural parallel

    MLPerf Inference Benchmark

    Authors
    Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu (47 authors in total)
    Year
    2020
    Venue
    ACM/IEEE ISCA 2020, pp. 446-459

    Korean review of T13-17

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. T14-5Structural parallelSince 2025

    Training LLMs for Generating IEC 61131-3 Structured Text with Online Feedback

    Authors
    Aaron Haag, Bertram Fuchs, Altay Kacan, Oliver Lohse
    Year
    2025
    Venue
    LLM4Code Workshop @ ICSE 2025

    Korean review of T14-5

  2. T14-3Structural parallel

    LLM4PLC: Harnessing Large Language Models for Verifiable Programming of PLCs in Industrial Control Systems

    Authors
    Mohamad Fakih, Rahul Dharmaji, Yasamin Moghaddas, Gustavo Quiros Araya, Oluwatosin Ogundare, Mohammad Abdullah Al Faruque
    Year
    2024
    Venue
    ICSE 2024 SEIP

    Korean review of T14-3

  3. T14-10Structural parallel

    Automated Attack Synthesis by Extracting Finite State Machines from Protocol Specification Documents

    Authors
    Maria Leonor Pacheco, Max von Hippel, Ben Weintraub, Dan Goldwasser, Cristina Nita-Rotaru
    Year
    2022
    Venue
    IEEE Symposium on Security and Privacy (S&P) 2022

    Korean review of T14-10

  4. T14-11Structural parallel

    Syntax-Guided Synthesis

    Authors
    Rajeev Alur, Rastislav Bodik, Garvit Juniwal, Milo M. K. Martin, Mukund Raghothaman, Sanjit A. Seshia, Rishabh Singh, Armando Solar-Lezama, Emina Torlak, Abhishek Udupa
    Year
    2013
    Venue
    FMCAD 2013 (Formal Methods in Computer-Aided Design), pp. 1-8

    Korean review of T14-11

  5. T14-12Structural parallel

    Automating string processing in spreadsheets using input-output examples

    Authors
    Sumit Gulwani (Microsoft Research)
    Year
    2011
    Venue
    POPL 2011 (38th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages), pp. 317-330

    Korean review of T14-12

  6. T14-13Structural parallel

    Combinatorial Sketching for Finite Programs

    Authors
    Armando Solar-Lezama, Liviu Tancau, Rastislav Bodik, Vijay Saraswat, Sanjit Seshia
    Year
    2006
    Venue
    ASPLOS 2006 (12th International Conference on Architectural Support for Programming Languages and Operating Systems), pp. 404-415

    Korean review of T14-13

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. T15-2.10Structural parallelSince 2025

    ESP32-Based Sparkplug B Gateway Framework for Brownfield PLC Integration into an IIoT Unified Namespace: A Data Foundation for Intelligent Industrial Systems

    Authors
    Ivana Šenk, Srđan Tegeltija, Laslo Tarjan
    Year
    2026
    Venue
    Electronics 15(15), 3441, 2026

    Korean review of T15-2.10

  2. T15-2.3Structural parallel

    Reusing OPC UA information models in the Asset Administration Shell

    Authors
    Arno Weiss, Dirk Reichelt
    Year
    2023
    Venue
    2023 IEEE 21st International Conference on Industrial Informatics (INDIN)

    Korean review of T15-2.3

  3. T15-2.5Structural parallel

    Evaluation and Extension of OPC UA Publish/Subscribe MQTT Binding

    Authors
    Hannes Raddatz, Eman Mahmoud, Fabian Hölzke, Peter Danielis, Dirk Timmermann, Frank Golatowski
    Year
    2020
    Venue
    2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS), pp.543-548, 2020-06

    Korean review of T15-2.5

  4. T15-2.8Structural parallel

    File- and API-based interoperability of digital twins by model transformation: An IIoT case study using asset administration shell

    Authors
    Marie Platenius-Mohr, Somayeh Malakuti, Sten Grüner, Johannes Schmitt, Thomas Goldschmidt
    Year
    2020
    Venue
    Future Generation Computer Systems, vol.113, pp.94-105, 2020-12

    Korean review of T15-2.8

  5. T15-2.11Structural parallel

    A Cyber-Physical Machine Tools Platform using OPC UA and MTConnect

    Authors
    Chao Liu, Hrishikesh Vengayil, Yuqian Lu, Xun Xu
    Year
    2019
    Venue
    Journal of Manufacturing Systems, vol.51, pp.61-74, 2019-04

    Korean review of T15-2.11

T16. Manufacturing knowledge graphs and semantic layers

Research on giving plant data a shared meaning across systems.

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  1. T16-6Structural parallelSince 2025

    Knowledge Graphs as the Missing Data Layer for LLM-Based Industrial Asset Operations

    Authors
    Madhulatha Mandarapu, Sandeep Kunkunuru
    Year
    2026
    Venue
    Agents+Graph (AG2026) workshop, VLDB 2026

    Korean review of T16-6

  2. T16-1Structural parallel

    The Industrial Ontologies Foundry (IOF) Core Ontology

    Authors
    Boonserm Kulvatunyou, Milos Drobnjakovic, Farhad Ameri, Chris Will, Barry Smith
    Year
    2022
    Venue
    Formal Ontologies Meet Industry (FOMI) 2022,, 2022-09-12~15

    Korean review of T16-1

  3. T16-2Structural parallel

    Semantic Integration of Bosch Manufacturing Data Using Virtual Knowledge Graphs

    Authors
    Elem Guzel Kalayci, Irlan Grangel Gonzalez, Felix Losch, Guohui Xiao, Anees ul Mehdi, Evgeny Kharlamov, Diego Calvanese
    Year
    2020
    Venue
    ISWC 2020 (19th International Semantic Web Conference), LNCS 12507, 464~pp. 481

    Korean review of T16-2

  4. T16-5Structural parallel

    Generation of Asset Administration Shell with Large Language Model Agents

    Authors
    Yuchen Xia, Zhewen Xiao, Nasser Jazdi, Michael Weyrich
    Year
    2024
    Venue
    IEEE Access

    Korean review of T16-5

  5. T16-9Structural parallel

    Ontop: Answering SPARQL queries over relational databases

    Authors
    Diego Calvanese, Benjamin Cogrel, Sarah Komla-Ebri, Roman Kontchakov, Davide Lanti, Martin Rezk, Mariano Rodriguez-Muro, Guohui Xiao
    Year
    2017
    Venue
    Semantic Web Journal, vol. 8 no. 3, 471~pp. 487

    Korean review of T16-9

  6. T16-10Structural parallel

    RML: A Generic Language for Integrated RDF Mappings of Heterogeneous Data

    Authors
    Anastasia Dimou, Miel Vander Sande, Pieter Colpaert, Ruben Verborgh, Erik Mannens, Rik Van de Walle
    Year
    2014
    Venue
    Linked Data on the Web (LDOW 2014),, 2014-04-08, CEUR-WS Vol-1184

    Korean review of T16-10

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. T17-9Structural parallelSince 2025

    MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL

    Authors
    Bing Wang, Changyu Ren, Jian Yang, Xinnian Liang, Jiaqi Bai, LinZheng Chai, Zhao Yan, Qian-Wen Zhang, Di Yin, Xing Sun, Zhoujun Li
    Year
    2025
    Venue
    COLING 2025

    Korean review of T17-9

  2. T17-3Structural parallel

    Semantic Evaluation for Text-to-SQL with Distilled Test Suites

    Authors
    Ruiqi Zhong, Tao Yu, Dan Klein
    Year
    2020
    Venue
    EMNLP 2020 (Long Paper)

    Korean review of T17-3

  3. T17-6Structural parallel

    RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers

    Authors
    Bailin Wang, Richard Shin, Xiaodong Liu, Oleksandr Polozov, Matthew Richardson
    Year
    2020
    Venue
    ACL 2020 (Long Paper), pp. 7567-7578

    Korean review of T17-6

  4. T17-7Structural parallel

    DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction

    Authors
    Mohammadreza Pourreza, Davood Rafiei
    Year
    2023
    Venue
    NeurIPS 2023

    Korean review of T17-7

  5. T17-8Structural parallel

    Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation

    Authors
    Dawei Gao, Haibin Wang, Yaliang Li, Xiuyu Sun, Yichen Qian, Bolin Ding, Jingren Zhou
    Year
    2024
    Venue
    Proceedings of the VLDB Endowment vol. 17 no. 5 (2024) pp. 1132-1145

    Korean review of T17-8

  6. T17-10Structural parallel

    CHESS: Contextual Harnessing for Efficient SQL Synthesis

    Authors
    Shayan Talaei, Mohammadreza Pourreza, Yu-Chen Chang, Azalia Mirhoseini, Amin Saberi
    Year
    2024
    Venue
    arXiv

    Korean review of T17-10

  7. T17-13Structural parallel

    Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models

    Authors
    Bernd Bohnet, Vinh Q
    Year
    2023
    Venue
    arXiv

    Korean review of T17-13

  8. T17-14Structural parallel

    RARR: Researching and Revising What Language Models Say, Using Language Models

    Authors
    Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, Kelvin Guu
    Year
    2023
    Venue
    ACL 2023 (Long Paper), pp. 16477-16508

    Korean review of T17-14

  9. T17-16Structural parallel

    FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

    Authors
    Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi
    Year
    2023
    Venue
    EMNLP 2023

    Korean review of T17-16

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. T18-12Structural parallelSince 2025

    Provenance Tracking in Large-Scale Machine Learning Systems

    Authors
    Gabriele Padovani, Valentine Anantharaj, Sandro Fiore
    Year
    2025
    Venue
    ICPP Workshops 2025

    Korean review of T18-12

  2. T18-2Structural parallel

    The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction

    Authors
    Eric Breck, Shanqing Cai, Eric Nielsen, Michael Salib, D. Sculley
    Year
    2017
    Venue
    IEEE Big Data

    Korean review of T18-2

  3. T18-3Structural parallel

    Data Validation for Machine Learning

    Authors
    Neoklis Polyzotis, Martin Zinkevich, Sudip Roy, Eric Breck, Steven Whang
    Year
    2019
    Venue
    MLSys(Proceedings of Machine Learning and Systems) 1

    Korean review of T18-3

  4. T18-6Structural parallel

    Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing

    Authors
    Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, Parker Barnes
    Year
    2020
    Venue
    ACM FAT* 2020

    Korean review of T18-6

  5. T18-9Structural parallel

    Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift

    Authors
    Stephan Rabanser, Stephan Günnemann, Zachary C. Lipton
    Year
    2019
    Venue
    NeurIPS 2019 (Advances in Neural Information Processing Systems 32)

    Korean review of T18-9

From research to product use

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

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