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2020 – today
- 2024
- [c74]Erik Jones, Hamid Palangi, Clarisse Simões, Varun Chandrasekaran, Subhabrata Mukherjee, Arindam Mitra, Ahmed Hassan Awadallah, Ece Kamar:
Teaching Language Models to Hallucinate Less with Synthetic Tasks. ICLR 2024 - [c73]Mert Yüksekgönül, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi:
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models. ICLR 2024 - [i36]Susan Landau, James X. Dempsey, Ece Kamar, Steven M. Bellovin:
Recommendations for Government Development and Use of Advanced Automated Systems to Make Decisions about Individuals. CoRR abs/2403.01649 (2024) - [i35]Susan Landau, James X. Dempsey, Ece Kamar, Steven M. Bellovin, Robert Pool:
Challenging the Machine: Contestability in Government AI Systems. CoRR abs/2406.10430 (2024) - 2023
- [c72]John Joon Young Chung, Ece Kamar, Saleema Amershi:
Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions. ACL (1) 2023: 575-593 - [i34]Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott M. Lundberg, Harsha Nori, Hamid Palangi, Marco Túlio Ribeiro, Yi Zhang:
Sparks of Artificial General Intelligence: Early experiments with GPT-4. CoRR abs/2303.12712 (2023) - [i33]John Joon Young Chung, Ece Kamar, Saleema Amershi:
Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions. CoRR abs/2306.04140 (2023) - [i32]Mert Yüksekgönül, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi:
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models. CoRR abs/2309.15098 (2023) - [i31]Erik Jones, Hamid Palangi, Clarisse Simões, Varun Chandrasekaran, Subhabrata Mukherjee, Arindam Mitra, Ahmed Awadallah, Ece Kamar:
Teaching Language Models to Hallucinate Less with Synthetic Tasks. CoRR abs/2310.06827 (2023) - 2022
- [j7]Sandhya Saisubramanian, Ece Kamar, Shlomo Zilberstein:
Avoiding Negative Side Effects of Autonomous Systems in the Open World. J. Artif. Intell. Res. 74: 143-177 (2022) - [c71]Andi Peng, Besmira Nushi, Emre Kiciman, Kori Inkpen, Ece Kamar:
Investigations of Performance and Bias in Human-AI Teamwork in Hiring. AAAI 2022: 12089-12097 - [c70]Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, Ece Kamar:
ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection. ACL (1) 2022: 3309-3326 - [c69]Ya'akov (Kobi) Gal, Avi Segal
, Ece Kamar, Eric Horvitz, Chris J. Lintott, Mike Walmsley:
A new Workflow for Human-AI Collaboration in Citizen Science. GoodIT 2022: 89-95 - [i30]Andi Peng, Besmira Nushi, Emre Kiciman, Kori Inkpen, Ece Kamar:
Investigations of Performance and Bias in Human-AI Teamwork in Hiring. CoRR abs/2202.11812 (2022) - [i29]Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, Ece Kamar:
ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection. CoRR abs/2203.09509 (2022) - [i28]Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David C. Parkes, William H. Press
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence. CoRR abs/2211.06318 (2022) - [i27]Tejas Gokhale, Hamid Palangi, Besmira Nushi, Vibhav Vineet, Eric Horvitz, Ece Kamar, Chitta Baral, Yezhou Yang:
Benchmarking Spatial Relationships in Text-to-Image Generation. CoRR abs/2212.10015 (2022) - 2021
- [j6]Sandhya Saisubramanian, Shlomo Zilberstein, Ece Kamar:
Avoiding Negative Side Effects Due to Incomplete Knowledge of AI Systems. AI Mag. 42(4): 62-71 (2021) - [c68]Jonathan Martinez, Kobi Gal, Ece Kamar, Levi H. S. Lelis:
Improving the Performance-Compatibility Tradeoff with Personalized Objective Functions. AAAI 2021: 5967-5974 - [c67]Gagan Bansal, Besmira Nushi, Ece Kamar, Eric Horvitz, Daniel S. Weld:
Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork. AAAI 2021: 11405-11414 - [c66]Solon Barocas
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. AIES 2021: 368-378 - [c65]Joon Sung Park, Michael S. Bernstein
Understanding the Representation and Representativeness of Age in AI Data Sets. AIES 2021: 834-842 - [c64]Gagan Bansal, Tongshuang Wu, Joyce Zhou, Raymond Fok, Besmira Nushi, Ece Kamar, Marco Túlio Ribeiro, Daniel S. Weld:
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance. CHI 2021: 81:1-81:16 - [c63]Sahil Singla, Besmira Nushi, Shital Shah, Ece Kamar, Eric Horvitz:
Understanding Failures of Deep Networks via Robust Feature Extraction. CVPR 2021: 12853-12862 - [c62]Joon Sung Park, Danielle Bragg, Ece Kamar, Meredith Ringel Morris:
Designing an Online Infrastructure for Collecting AI Data From People With Disabilities. FAccT 2021: 52-63 - [e1]Ece Kamar, Kurt Luther:
Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021, virtual, November 14-18, 2021. AAAI Press 2021, ISBN 978-1-57735-872-5 [contents] - [i26]Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach:
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. CoRR abs/2103.06076 (2021) - [i25]Joon Sung Park, Michael S. Bernstein, Robin N. Brewer, Ece Kamar, Meredith Ringel Morris:
Understanding the Representation and Representativeness of Age in AI Data Sets. CoRR abs/2103.09058 (2021) - [i24]Ramya Ramakrishnan, Vaibhav V. Unhelkar
A Bayesian Approach to Identifying Representational Errors. CoRR abs/2103.15171 (2021) - 2020
- [j5]Ramya Ramakrishnan, Ece Kamar, Debadeepta Dey, Eric Horvitz, Julie Shah:
Blind Spot Detection for Safe Sim-to-Real Transfer. J. Artif. Intell. Res. 67: 191-234 (2020) - [j4]Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris:
Toward fairness in AI for people with disabilities SBG@a research roadmap. ACM SIGACCESS Access. Comput. 125: 2 (2020) - [c61]Zheng Wang, Bruno D. Abrahao, Ece Kamar:
Supervised Discovery of Unknown Unknowns through Test Sample Mining (Student Abstract). AAAI 2020: 13959-13960 - [c60]Sandhya Saisubramanian, Ece Kamar, Shlomo Zilberstein:
Mitigating the Negative Side Effects of Reasoning with Imperfect Models: A Multi-Objective Approach. AAMAS 2020: 1984-1986 - [c59]Keri Mallari, Kori Inkpen, Paul Johns, Sarah Tan, Divya Ramesh, Ece Kamar:
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism. CHI 2020: 1-13 - [c58]Ramprasaath R. Selvaraju, Purva Tendulkar, Devi Parikh, Eric Horvitz, Marco Túlio Ribeiro, Besmira Nushi, Ece Kamar:
SQuINTing at VQA Models: Introspecting VQA Models With Sub-Questions. CVPR 2020: 10000-10008 - [c57]Sandhya Saisubramanian, Ece Kamar, Shlomo Zilberstein:
A Multi-Objective Approach to Mitigate Negative Side Effects. IJCAI 2020: 354-361 - [c56]Bryan Wilder, Eric Horvitz, Ece Kamar:
Learning to Complement Humans. IJCAI 2020: 1526-1533 - [c55]Megha Srivastava, Besmira Nushi, Ece Kamar, Shital Shah, Eric Horvitz:
An Empirical Analysis of Backward Compatibility in Machine Learning Systems. KDD 2020: 3272-3280 - [c54]Anthony Z. Liu, Santiago Guerra, Isaac Fung, Gabriel Matute, Ece Kamar, Walter S. Lasecki:
Towards Hybrid Human-AI Workflows for Unknown Unknown Detection. WWW 2020: 2432-2442 - [i23]Ramprasaath R. Selvaraju, Purva Tendulkar, Devi Parikh, Eric Horvitz, Marco Ribeiro, Besmira Nushi, Ece Kamar:
SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions. CoRR abs/2001.06927 (2020) - [i22]Keri Mallari, Kori Inkpen, Paul Johns, Sarah Tan, Divya Ramesh, Ece Kamar:
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism. CoRR abs/2002.01111 (2020) - [i21]Jonathan Martinez, Kobi Gal, Ece Kamar, Levi H. S. Lelis:
Personalization in Human-AI Teams: Improving the Compatibility-Accuracy Tradeoff. CoRR abs/2004.02289 (2020) - [i20]Gagan Bansal, Besmira Nushi, Ece Kamar, Eric Horvitz, Daniel S. Weld:
Optimizing AI for Teamwork. CoRR abs/2004.13102 (2020) - [i19]Bryan Wilder, Eric Horvitz, Ece Kamar:
Learning to Complement Humans. CoRR abs/2005.00582 (2020) - [i18]Gagan Bansal, Tongshuang Wu, Joyce Zhou, Raymond Fok, Besmira Nushi, Ece Kamar, Marco Túlio Ribeiro, Daniel S. Weld:
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance. CoRR abs/2006.14779 (2020) - [i17]Ivan Evtimov, Weidong Cui, Ece Kamar, Emre Kiciman, Tadayoshi Kohno, Jerry Li:
Security and Machine Learning in the Real World. CoRR abs/2007.07205 (2020) - [i16]Megha Srivastava, Besmira Nushi, Ece Kamar, Shital Shah, Eric Horvitz:
An Empirical Analysis of Backward Compatibility in Machine Learning Systems. CoRR abs/2008.04572 (2020) - [i15]Sandhya Saisubramanian, Shlomo Zilberstein, Ece Kamar:
Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems. CoRR abs/2008.12146 (2020) - [i14]Sahil Singla, Besmira Nushi, Shital Shah, Ece Kamar, Eric Horvitz:
Understanding Failures of Deep Networks via Robust Feature Extraction. CoRR abs/2012.01750 (2020) - [i13]Kaivalya Rawal, Ece Kamar, Himabindu Lakkaraju:
Can I Still Trust You?: Understanding the Impact of Distribution Shifts on Algorithmic Recourses. CoRR abs/2012.11788 (2020)
2010 – 2019
- 2019
- [j3]Iyad Rahwan, Manuel Cebrián
Machine behaviour. Nat. 568(7753): 477-486 (2019) - [c53]Gagan Bansal, Besmira Nushi, Ece Kamar, Daniel S. Weld, Walter S. Lasecki, Eric Horvitz:
Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff. AAAI 2019: 2429-2437 - [c52]Ramya Ramakrishnan, Ece Kamar, Besmira Nushi, Debadeepta Dey, Julie Shah, Eric Horvitz:
Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution. AAAI 2019: 6137-6145 - [c51]Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Jure Leskovec
Faithful and Customizable Explanations of Black Box Models. AIES 2019: 131-138 - [c50]Gagan Bansal, Besmira Nushi, Ece Kamar, Walter S. Lasecki, Daniel S. Weld, Eric Horvitz:
Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance. HCOMP 2019: 2-11 - [c49]Shayan Doroudi, Ece Kamar, Emma Brunskill:
Not Everyone Writes Good Examples but Good Examples Can Come from Anywhere. HCOMP 2019: 12-21 - [c48]Andi Peng, Besmira Nushi, Emre Kiciman, Kori Inkpen, Siddharth Suri, Ece Kamar:
What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring. HCOMP 2019: 125-134 - [c47]Saleema Amershi, Andrew Begel, Christian Bird, Robert DeLine, Harald C. Gall
Software engineering for machine learning: a case study. ICSE (SEIP) 2019: 291-300 - [c46]Yongsung Kim, Adam Fourney
Studying Preferences and Concerns about Information Disclosure in Email Notifications. WWW 2019: 874-885 - [i12]Gagan Bansal, Besmira Nushi, Ece Kamar, Daniel S. Weld, Walter S. Lasecki, Eric Horvitz:
A Case for Backward Compatibility for Human-AI Teams. CoRR abs/1906.01148 (2019) - [i11]Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris:
Toward Fairness in AI for People with Disabilities: A Research Roadmap. CoRR abs/1907.02227 (2019) - [i10]Andi Peng, Besmira Nushi, Emre Kiciman, Kori Inkpen, Siddharth Suri, Ece Kamar:
What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring. CoRR abs/1909.03567 (2019) - 2018
- [c45]Avi Segal, Kobi Gal, Ece Kamar, Eric Horvitz, Grant Miller:
Optimizing Interventions via Offline Policy Evaluation: Studies in Citizen Science. AAAI 2018: 1536-1544 - [c44]Ramya Ramakrishnan, Ece Kamar, Debadeepta Dey, Julie A. Shah, Eric Horvitz:
Discovering Blind Spots in Reinforcement Learning. AAMAS 2018: 1017-1025 - [c43]Besmira Nushi, Ece Kamar, Eric Horvitz:
Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure. HCOMP 2018: 126-135 - [c42]Elliot Salisbury, Ece Kamar, Meredith Ringel Morris:
Evaluating and Complementing Vision-to-Language Technology for People who are Blind with Conversational Crowdsourcing. IJCAI 2018: 5349-5353 - [i9]Ramya Ramakrishnan, Ece Kamar, Debadeepta Dey, Julie A. Shah, Eric Horvitz:
Discovering Blind Spots in Reinforcement Learning. CoRR abs/1805.08966 (2018) - [i8]Yongsung Kim, Adam Fourney
Studying Preferences and Concerns about Information Disclosure in Email Notifications. CoRR abs/1808.00356 (2018) - [i7]Sarah Tan, Julius Adebayo, Kori Inkpen, Ece Kamar:
Investigating Human + Machine Complementarity for Recidivism Predictions. CoRR abs/1808.09123 (2018) - [i6]Besmira Nushi, Ece Kamar, Eric Horvitz:
Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure. CoRR abs/1809.07424 (2018) - 2017
- [c41]Ece Kamar, Lydia Manikonda:
Complementing the Execution of AI Systems with Human Computation. AAAI Workshops 2017 - [c40]Besmira Nushi, Ece Kamar, Eric Horvitz, Donald Kossmann:
On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems. AAAI 2017: 1017-1025 - [c39]Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Eric Horvitz:
Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration. AAAI 2017: 2124-2132 - [c38]Joseph Chee Chang, Saleema Amershi, Ece Kamar:
Revolt: Collaborative Crowdsourcing for Labeling Machine Learning Datasets. CHI 2017: 2334-2346 - [c37]Niloufar Salehi, Jaime Teevan, Shamsi T. Iqbal, Ece Kamar:
Communicating Context to the Crowd for Complex Writing Tasks. CSCW 2017: 1890-1901 - [c36]Harmanpreet Kaur, Mitchell L. Gordon, Yiwei Yang, Jeffrey P. Bigham, Jaime Teevan, Ece Kamar, Walter S. Lasecki:
CrowdMask: Using Crowds to Preserve Privacy in Crowd-Powered Systems via Progressive Filtering. HCOMP 2017: 89-97 - [c35]Elliot Salisbury, Ece Kamar, Meredith Ringel Morris:
Toward Scalable Social Alt Text: Conversational Crowdsourcing as a Tool for Refining Vision-to-Language Technology for the Blind. HCOMP 2017: 147-156 - [c34]Amulya Yadav, Aida Rahmattalabi, Ece Kamar, Phebe Vayanos, Milind Tambe, Venil Loyd Noronha:
Explanation Systems for Influence Maximization Algorithms. SocInf@IJCAI 2017: 8-19 - [c33]Sean Andrist, Dan Bohus, Ece Kamar, Eric Horvitz:
What Went Wrong and Why? Diagnosing Situated Interaction Failures in the Wild. ICSR 2017: 293-303 - [i5]Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Jure Leskovec:
Interpretable & Explorable Approximations of Black Box Models. CoRR abs/1707.01154 (2017) - 2016
- [j2]Ece Kamar:
Hybrid workplaces of the future. XRDS 23(2): 22-25 (2016) - [c32]Amulya Yadav, Hau Chan, Albert Xin Jiang, Eric Rice, Ece Kamar, Barbara J. Grosz, Milind Tambe:
POMDPs for Assisting Homeless Shelters - Computational and Deployment Challenges. AAMAS Workshops (Visionary Papers) 2016: 67-87 - [c31]Amulya Yadav, Ece Kamar, Barbara J. Grosz, Milind Tambe:
HEALER: POMDP Planning for Scheduling Interventions among Homeless Youth (Demonstration). AAMAS 2016: 1504-1506 - [c30]Shayan Doroudi
Toward a Learning Science for Complex Crowdsourcing Tasks. CHI 2016: 2623-2634 - [c29]Ofra Amir, Ece Kamar, Andrey Kolobov, Barbara J. Grosz:
Interactive Teaching Strategies for Agent Training. IJCAI 2016: 804-811 - [c28]Avi Segal, Ya'akov (Kobi) Gal, Ece Kamar, Eric Horvitz, Alex Bowyer, Grant Miller:
Intervention Strategies for Increasing Engagement in Crowdsourcing: Platform, Predictions, and Experiments. IJCAI 2016: 3861-3867 - [c27]Ece Kamar:
Directions in Hybrid Intelligence: Complementing AI Systems with Human Intelligence. IJCAI 2016: 4070-4073 - [c26]Cathy Wu, Ece Kamar, Eric Horvitz:
Clustering for set partitioning with a case study in ridesharing. ITSC 2016: 1384-1388 - [c25]Cathy Wu, Kalyanaraman Shankari, Ece Kamar, Randy H. Katz, David E. Culler, Christos H. Papadimitriou, Eric Horvitz, Alexandre M. Bayen:
Optimizing the diamond lane: A more tractable carpool problem and algorithms. ITSC 2016: 1389-1396 - [i4]Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Eric Horvitz:
Discovering Blind Spots of Predictive Models: Representations and Policies for Guided Exploration. CoRR abs/1610.09064 (2016) - [i3]Besmira Nushi, Ece Kamar, Eric Horvitz, Donald Kossmann:
On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems. CoRR abs/1611.08309 (2016) - 2015
- [c24]Ece Kamar, Eric Horvitz:
Planning for Crowdsourcing Hierarchical Tasks. AAMAS 2015: 1191-1199 - [c23]Ece Kamar, Ashish Kapoor, Eric Horvitz:
Identifying and Accounting for Task-Dependent Bias in Crowdsourcing. HCOMP 2015: 92-101 - [c22]Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz:
Metareasoning for Planning Under Uncertainty. IJCAI 2015: 1601-1609 - [i2]Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz:
Metareasoning for Planning Under Uncertainty. CoRR abs/1505.00399 (2015) - 2014
- [c21]Adish Singla
Stochastic Privacy. AAAI 2014: 152-158 - [c20]Christopher H. Lin, Ece Kamar, Eric Horvitz:
Signals in the Silence: Models of Implicit Feedback in a Recommendation System for Crowdsourcing. AAAI 2014: 908-915 - [c19]Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor:
Gauss meets Canadian traveler: shortest-path problems with correlated natural dynamics. AAMAS 2014: 1101-1108 - [c18]Walter S. Lasecki, Jaime Teevan, Ece Kamar:
Information extraction and manipulation threats in crowd-powered systems. CSCW 2014: 248-256 - [c17]Margaret Mitchell, Dan Bohus, Ece Kamar:
Crowdsourcing Language Generation Templates for Dialogue Systems. INLG 2014: 16-24 - [i1]Adish Singla, Eric Horvitz, Ece Kamar, Ryen White:
Stochastic Privacy. CoRR abs/1404.5454 (2014) - 2013
- [j1]Ece Kamar, Ya'akov (Kobi) Gal
Modeling information exchange opportunities for effective human-computer teamwork. Artif. Intell. 195: 528-550 (2013) - [c16]Ece Kamar, Eric Horvitz:
Light at the end of the tunnel: a Monte Carlo approach to computing value of information. AAMAS 2013: 571-578 - [c15]Andrew Mao, Ece Kamar, Yiling Chen, Eric Horvitz, Megan E. Schwamb, Chris J. Lintott, Arfon M. Smith:
Volunteering Versus Work for Pay: Incentives and Tradeoffs in Crowdsourcing. HCOMP 2013: 94-102 - [c14]Andrew Mao, Ece Kamar, Eric Horvitz:
Why Stop Now? Predicting Worker Engagement in Online Crowdsourcing. HCOMP 2013: 103-111 - [c13]Ece Kamar, Ashish Kapoor, Eric Horvitz:
Lifelong Learning for Acquiring the Wisdom of the Crowd. IJCAI 2013: 2313-2320 - [c12]Stephanie Rosenthal, Dan Bohus, Ece Kamar, Eric Horvitz:
Look versus Leap: Computing Value of Information with High-Dimensional Streaming Evidence. IJCAI 2013: 2561-2567 - 2012
- [c11]Ece Kamar, Severin Hacker, Eric Horvitz:
Combining human and machine intelligence in large-scale crowdsourcing. AAMAS 2012: 467-474 - [c10]Ece Kamar, Eric Horvitz:
Incentives for truthful reporting in crowdsourcing. AAMAS 2012: 1329-1330 - [c9]Dan Bohus, Ece Kamar, Eric Horvitz:
Towards Situated Collaboration. SDCTD@NAACL-HLT 2012: 13-14 - [c8]William Yang Wang, Dan Bohus, Ece Kamar, Eric Horvitz:
Crowdsourcing the acquisition of natural language corpora: Methods and observations. SLT 2012: 73-78 - 2011
- [c7]Ece Kamar, Eric Horvitz:
Jogger: models for context-sensitive reminding. AAMAS 2011: 1089-1090 - [c6]Paul Bennett, Ece Kamar, Gabriella Kazai:
MSRC at TREC 2011 Crowdsourcing Track. TREC 2011
2000 – 2009
- 2009
- [c5]Ece Kamar, Ya'akov Gal, Barbara J. Grosz:
Incorporating helpful behavior into collaborative planning. AAMAS (2) 2009: 875-882 - [c4]Ece Kamar, Ya'akov Gal
Modeling User Perception of Interaction Opportunities for Effective Teamwork. CSE (4) 2009: 271-277 - [c3]Ece Kamar, Eric Horvitz:
Collaboration and Shared Plans in the Open World: Studies of Ridesharing. IJCAI 2009: 187 - 2008
- [c2]Ece Kamar, Eric Horvitz, Christopher Meek:
Mobile opportunistic commerce: mechanisms, architecture, and application. AAMAS (2) 2008: 1087-1094 - 2007
- [c1]Ece Kamar, Barbara J. Grosz, David Sarne:
Modeling User Perception of Interaction Opportunities in Collaborative Human-Computer Settings. AAAI 2007: 1872-1873
Coauthor Index
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