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Planning a trip into a potentially unsafe area is a difficult task.
Information foraging
Peter Pirolli and Stuart Card. 1999 · 1999
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Language Models are Few-Shot Learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2005
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The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. In Proceedings of International Conference on Intelligence Analysis , Vol. 5. 2–4
Peter Pirolli and Stuart Card. 2005 · 2005
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Fear and Danger in Nocturnal Urban Environments. In Proceedings of the 22nd Conference of the Computer-Human Interaction Special Interest Group of Australia on Computer-Human Interaction (OZCHI ’10) . Association for Computing Machinery, New York, NY, USA, 380–383
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Welcome to the Jungle: HCI after Dark. In CHI ’11 Extended Abstracts on Human Factors in Computing Systems (CHI EA ’11) . Association for Computing Machinery, New York, NY, USA, 753–762
Christine Satchell and Marcus Foth. 2011 · 2011
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Improving the Safety of Homeless Young People with Mobile Phones: Values, Form and Function. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’11) . Association for Computing Machinery, New York, NY, USA, 1707–1716
Jill Palzkill Woelfer, Amy Iverson, David G. Hendry, Batya Friedman, and Brian T. Gill. 2011 · 2011
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Safe Mathare: A Mobile System for Women’s Safe Commutes in the Slums. In Proceedings of the 14th International Conference on Human-Computer Interaction with Mobile Devices and Services Companion (MobileHCI ’12) . Association for Computing Machinery, New York, NY, USA, 47–52
Margaret Hagan, Nan Zhang, and Joseph ’Jofish’ Kaye. 2012 · 2012
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Crime Applications and Social Machines: Crowdsourcing Sensitive Data. In Proceedings of the 22nd International Conference on World Wide Web (WWW ’13 Companion) . Association for Computing Machinery, New York, NY, USA, 891–896
Maire Byrne Evans, Kieron O’Hara, Thanassis Tiropanis, and Craig Webber. 2013 · 2013
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The Search Strategies of Smartphone Users for Tourism Information: A Reflection of Big Data. In Proceedings of the ASE BigData & SocialInformatics 2015 (ASE BD&SI ’15) . Association for Computing Machinery, New York, NY, USA, Article 61, 6 pages
Chaang-Iuan Ho and Yu-Lan Yuan. 2015 · 2015
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Digital Neighborhood Watch: To Share or Not to Share?. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA ’16) . Association for Computing Machinery, New York, NY, USA, 2148–2155
Cristina Kadar, Yiea-Funk Te, Raquel Rosés Brüngger, and Irena Pletikosa Cvijikj. 2016 · 2016
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Software 2.0
Andrej Karpathy. 2017 · 2017
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Women’s Safety in Public Spaces: Examining the Efficacy of Panic Buttons in New Delhi. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI ’17) . Association for Computing Machinery, New York, NY, USA, 3340–3351
Naveena Karusala and Neha Kumar. 2017 · 2017
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Trends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18) . Association for Computing Machinery, New York, NY, USA, 1–18
Ashraf Abdul, Jo Vermeulen, Danding Wang, Brian Y. Lim, and Mohan Kankanhalli. 2018 · 2018
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Are social networking sites information sources? Informational purposes of high-school students in using SNSs
Karine Aillerie and Sarah McNicol. 2018 · 2018
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Reliability and Inter-Rater Reliability in Qualitative Research: Norms and Guidelines for CSCW and HCI Practice
Nora McDonald, Sarita Schoenebeck, and Andrea Forte. 2019 · 2019
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Designing Technology to Support Safety for Transgender Women & Non-Binary People of Color. In Companion Publication of the 2019 on Designing Interactive Systems Conference 2019 Companion (DIS ’19 Companion) . Association for Computing Machinery, New York, NY, USA, 289–294
Denny L. Starks, Tawanna Dillahunt, and Oliver L. Haimson. 2019 · 2019
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Retrieval-augmented generation for knowledge-intensive NLP tasks. In Proceedings of the 34th International Conference on Neural Information Processing Systems (NIPS ’20) . Curran Associates Inc., Red Hook, NY, USA, Article 793, 16 pages
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. 2020 · 2020
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Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA ’21) . Association for Computing Machinery, New York, NY, USA, Article 314, 7 pages
Laria Reynolds and Kyle McDonell. 2021 · 2021
Cited alongside, same era.
Precise Event-level Prediction of Urban Crime Reveals Signature of Enforcement Bias
Victor Rotaru, Yi Huang, Timmy Li, James Evans, and Ishanu Chattopadhyay. 2021 · 2021
Cited alongside, same era.
It’s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Association for Computational Linguistics, Online, 2339–2352
Timo Schick and Hinrich Schütze. 2021 · 2021
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Calibrate Before Use: Improving Few-shot Performance of Language Models. In Proceedings of the 38th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 139) , Marina Meila and Tong Zhang (Eds.). PMLR, 12697–12706
Synergi: A Mixed-Initiative System for Scholarly Synthesis and Sensemaking. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST ’23) . Association for Computing Machinery, New York, NY, USA
Hyeonsu B. Kang, Sherry Tongshuang Wu, Joseph Chee Chang, and Aniket Kittur. 2023 · 2023
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Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task. In The Eleventh International Conference on Learning Representations
Kenneth Li, Aspen K Hopkins, David Bau, Fernanda Viégas, Hanspeter Pfister, and Martin Wattenberg. 2023 · 2023
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Self-Refine: Iterative Refinement with Self-Feedback
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, and Peter Clark. 2023 · 2023
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The Batch, issue 209
Andrew Ng. 2023 · 2023
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Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021 · 2021
Cited alongside, same era.
Information Needs of Essential Workers During the COVID-19 Pandemic
Marianne Aubin Le Quéré, Ting-Wei Chiang, Karen Levy, and Mor Naaman. 2022 · 2022
Cited alongside, same era.
Large Language Models are Zero-Shot Reasoners. In Advances in Neural Information Processing Systems , Vol. 35. 22199–22213
Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Can language models learn from explanations in context?. In Findings of the Association for Computational Linguistics (EMNLP 2022) . Association for Computational Linguistics, Abu Dhabi, United Arab Emirates, 537–563
Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, Kory Mathewson, Mh Tessler, Antonia Creswell, James McClelland, Jane Wang, and Felix Hill. 2022 · 2022
Cited alongside, same era.
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . Association for Computational Linguistics, Dublin, Ireland, 8086–8098
Yao Lu, Max Bartolo, Alastair Moore, Sebastian Riedel, and Pontus Stenetorp. 2022 · 2022
Cited alongside, same era.
Ignore Previous Prompt: Attack Techniques For Language Models
Fábio Perez and Ian Ribeiro. 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models. In Proceedings of the 36th International Conference on Neural Information Processing Systems (NIPS ’22) . Curran Associates Inc., Red Hook, NY, USA, Article 1800, 14 pages
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou. 2022 · 2022
Cited alongside, same era.
Shifting Trust: Examining How Trust and Distrust Emerge, Transform, and Collapse in COVID-19 Information Seeking. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ’22) . Association for Computing Machinery, New York, NY, USA, Article 78, 21 pages
Yixuan Zhang, Nurul Suhaimi, Nutchanon Yongsatianchot, Joseph D Gaggiano, Miso Kim, Shivani A Patel, Yifan Sun, Stacy Marsella, Jacqueline Griffin, and Andrea G Parker. 2022 · 2022
Cited alongside, same era.
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, and Yi Zhang. 2023 · 2023
Cited alongside, same era.
Bhargavi Paranjape, Scott Lundberg, Sameer Singh, Hannaneh Hajishirzi, Luke Zettlemoyer, and Marco Tulio Ribeiro. 2023 · 2023
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Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions
Pouya Pezeshkpour and Estevam Hruschka. 2023 · 2023
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Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, and Yoav Shoham. 2023 · 2023
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A Case Study in Engineering a Conversational Programming Assistant’s Persona 121-129. In Joint Proceedings of the IUI 2023 Workshops: HAI-GEN, ITAH, MILC, SHAI, SketchRec, SOCIALIZE co-located with the ACM International Conference on Intelligent User Interfaces (IUI 2023), Sydney, Australia, March 27-31, 2023 (CEUR Workshop Proceedings, Vol. 3359) , Alison Smith-Renner and Paul Taele (Eds.). CEUR-WS.org, 121–129
Steven I. Ross, Michael J. Muller, Fernando Martinez, Stephanie Houde, and Justin D. Weisz. 2023 · 2023
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In-Context Impersonation Reveals Large Language Models’ Strengths and Biases
Leonard Salewski, Stephan Alaniz, Isabel Rio-Torto, Eric Schulz, and Zeynep Akata. 2023 · 2023
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Self-Consistency Improves Chain of Thought Reasoning in Language Models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2023 · 2023
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Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L. Griffiths, Yuan Cao, and Karthik Narasimhan. 2023 · 2023
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Large Language Models Are Human-Level Prompt Engineers
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba. 2023 · 2023
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A developer’s guide to prompt engineering and LLMs
Albert Ziegler and John Berryman. 2023 · 2023
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Prompting Considered Harmful
Meredith Ringel Morris. 2024 · 2024
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Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering
Jonas Oppenlaender, Rhema Linder, and Johanna Silvennoinen. 2024 · 2024
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Sensemaking: What is it today?. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24) . Association for Computing Machinery, New York, NY, USA, Article 487, 5 pages
Daniel M. Russell, Laura Koesten, Aniket Kittur, Nitesh Goyal, and Michael Xieyang Liu. 2024 · 2024
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Don’t Do RAG: When Cache-Augmented Generation is All You Need for Knowledge Tasks
Brian J Chan, Chao-Ting Chen, Jui-Hung Cheng, and Hen-Hsen Huang. 2025 · 2025
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