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2020 – today
- 2024
[c124]Wichayaporn Wongkamjan, Feng Gu, Yanze Wang, Ulf Hermjakob, Jonathan May, Brandon M. Stewart, Jonathan K. Kummerfeld, Denis Peskoff, Jordan L. Boyd-Graber:
More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play. ACL (1) 2024: 12423-12441- [c123]Alvin Grissom II, Jo Shoemaker, Benjamin Goldman, Ruikang Shi, Craig Stewart, C. Anton Rytting, Leah Findlater, Jordan L. Boyd-Graber:
Rapidly Piloting Real-time Linguistic Assistance for Simultaneous Interpreters with Untrained Bilingual Surrogates. LREC/COLING 2024: 13548-13556 - [c122]Zongxia Li, Andrew Mao, Daniel Stephens, Pranav Goel, Emily Walpole, Alden Dima, Juan Fung, Jordan L. Boyd-Graber:
Improving the TENOR of Labeling: Re-evaluating Topic Models for Content Analysis. EACL (1) 2024: 840-859 - [c121]Ishani Mondal, Shwetha S, Anandhavelu Natarajan, Aparna Garimella, Sambaran Bandyopadhyay, Jordan L. Boyd-Graber:
Presentations by the Humans and For the Humans: Harnessing LLMs for Generating Persona-Aware Slides from Documents. EACL (1) 2024: 2664-2684 - [c120]Chenglei Si, Navita Goyal, Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daumé III, Jordan L. Boyd-Graber:
Large Language Models Help Humans Verify Truthfulness - Except When They Are Convincingly Wrong. NAACL-HLT 2024: 1459-1474 - [c119]Neha Srikanth, Rupak Sarkar, Heran Mane, Elizabeth Aparicio, Quynh C. Nguyen, Rachel Rudinger, Jordan L. Boyd-Graber:
Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering. NAACL-HLT 2024: 7253-7268 - [i64]Yoo Yeon Sung, Ishani Mondal, Jordan L. Boyd-Graber:
How the Advent of Ubiquitous Large Language Models both Stymie and Turbocharge Dynamic Adversarial Question Generation. CoRR abs/2401.11185 (2024) - [i63]Zongxia Li, Andrew Mao, Daniel Stephens, Pranav Goel, Emily Walpole, Alden Dima, Juan Fung, Jordan L. Boyd-Graber:
Beyond Automated Evaluation Metrics: Evaluating Topic Models On Practical Social Science Content Analysis Tasks. CoRR abs/2401.16348 (2024) - [i62]Zongxia Li, Ishani Mondal, Yijun Liang, Huy Nghiem, Jordan Lee Boyd-Graber:
PANDA (Pedantic ANswer-correctness Determination and Adjudication): Improving Automatic Evaluation for Question Answering and Text Generation. CoRR abs/2402.11161 (2024) - [i61]Matthew Shu, Nishant Balepur, Shi Feng, Jordan L. Boyd-Graber:
KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students. CoRR abs/2402.12291 (2024) - [i60]Wichayaporn Wongkamjan, Feng Gu, Yanze Wang, Ulf Hermjakob, Jonathan May, Brandon M. Stewart, Jonathan K. Kummerfeld, Denis Peskoff, Jordan Lee Boyd-Graber:
More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play. CoRR abs/2406.04643 (2024) - [i59]Xiyang Wu, Tianrui Guan, Dianqi Li, Shuaiyi Huang, Xiaoyu Liu, Xijun Wang, Ruiqi Xian, Abhinav Shrivastava, Furong Huang, Jordan Lee Boyd-Graber, Tianyi Zhou, Dinesh Manocha:
AUTOHALLUSION: Automatic Generation of Hallucination Benchmarks for Vision-Language Models. CoRR abs/2406.10900 (2024) - [i58]Nishant Balepur, Matthew Shu, Alexander Miserlis Hoyle, Alison Robey, Shi Feng, Seraphina Goldfarb-Tarrant, Jordan L. Boyd-Graber:
A SMART Mnemonic Sounds like "Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic Learning Stick. CoRR abs/2406.15352 (2024) - [i57]Yoo Yeon Sung, Eve Fleisig, Ishani Mondal, Jordan Lee Boyd-Graber:
ADVSCORE: A Metric for the Evaluation and Creation of Adversarial Benchmarks. CoRR abs/2406.16342 (2024) - 2023
- [c118]Sander Schulhoff, Jeremy Pinto, Anaum Khan, Louis-François Bouchard, Chenglei Si, Svetlina Anati, Valen Tagliabue, Anson Liu Kost, Christopher Carnahan, Jordan L. Boyd-Graber:
Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs Through a Global Prompt Hacking Competition. EMNLP 2023: 4945-4977 - [c117]Chenglei Si, Weijia Shi, Chen Zhao, Luke Zettlemoyer, Jordan L. Boyd-Graber:
Getting MoRE out of Mixture of Language Model Reasoning Experts. EMNLP (Findings) 2023: 8234-8249 - [c116]HyoJung Han, Jordan L. Boyd-Graber, Marine Carpuat:
Bridging Background Knowledge Gaps in Translation with Automatic Explicitation. EMNLP 2023: 9718-9735 - [c115]Yoo Yeon Sung, Jordan L. Boyd-Graber, Naeemul Hassan:
Not all Fake News is Written: A Dataset and Analysis of Misleading Video Headlines. EMNLP 2023: 16241-16258 - [c114]Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang, Jordan L. Boyd-Graber, Lijuan Wang:
Prompting GPT-3 To Be Reliable. ICLR 2023 - [e4]Anna Rogers, Jordan L. Boyd-Graber, Naoaki Okazaki:
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2023, Toronto, Canada, July 9-14, 2023. Association for Computational Linguistics 2023, ISBN 978-1-959429-72-2 [contents] - [e3]Anna Rogers, Jordan L. Boyd-Graber, Naoaki Okazaki:
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), ACL 2023, Toronto, Canada, July 9-14, 2023. Association for Computational Linguistics 2023 [contents] - [e2]Anna Rogers, Jordan L. Boyd-Graber, Naoaki Okazaki:
Findings of the Association for Computational Linguistics: ACL 2023, Toronto, Canada, July 9-14, 2023. Association for Computational Linguistics 2023, ISBN 978-1-959429-62-3 [contents] - [i56]Chenglei Si, Weijia Shi, Chen Zhao, Luke Zettlemoyer, Jordan L. Boyd-Graber:
Mixture of Prompt Experts for Generalizable and Interpretable Question Answering. CoRR abs/2305.14628 (2023) - [i55]Ishani Mondal, Michelle Yuan, Anandhavelu Natarajan, Aparna Garimella, Francis Ferraro, Andrew Blair-Stanek, Benjamin Van Durme, Jordan L. Boyd-Graber:
InteractiveIE: Towards Assessing the Strength of Human-AI Collaboration in Improving the Performance of Information Extraction. CoRR abs/2305.14659 (2023) - [i54]Samuel Barham, Orion Weller, Michelle Yuan, Kenton Murray, Mahsa Yarmohammadi, Zhengping Jiang, Siddharth Vashishtha, Alexander Martin
, Anqi Liu, Aaron Steven White, Jordan L. Boyd-Graber, Benjamin Van Durme:
MegaWika: Millions of reports and their sources across 50 diverse languages. CoRR abs/2307.07049 (2023) - [i53]Chenglei Si, Navita Goyal, Sherry Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daumé III, Jordan L. Boyd-Graber:
Large Language Models Help Humans Verify Truthfulness - Except When They Are Convincingly Wrong. CoRR abs/2310.12558 (2023) - [i52]Yoo Yeon Sung, Jordan L. Boyd-Graber, Naeemul Hassan:
Not all Fake News is Written: A Dataset and Analysis of Misleading Video Headlines. CoRR abs/2310.13859 (2023) - [i51]Kyle Seelman, Mozhi Zhang, Jordan L. Boyd-Graber:
Labeled Interactive Topic Models. CoRR abs/2311.09438 (2023) - [i50]Neha Srikanth, Rupak Sarkar, Rachel Rudinger, Jordan L. Boyd-Graber:
Towards Pragmatic Awareness in Question Answering: A Case Study in Maternal and Infant Health. CoRR abs/2311.09542 (2023) - [i49]Sander Schulhoff, Jeremy Pinto, Anaum Khan, Louis-François Bouchard, Chenglei Si, Svetlina Anati, Valen Tagliabue, Anson Liu Kost, Christopher Carnahan, Jordan L. Boyd-Graber:
Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition. CoRR abs/2311.16119 (2023) - [i48]HyoJung Han, Jordan Lee Boyd-Graber, Marine Carpuat:
Bridging Background Knowledge Gaps in Translation with Automatic Explicitation. CoRR abs/2312.01308 (2023) - 2022
- [c113]Fenfei Guo, Chen Zhang, Zhirui Zhang, Qixin He, Kejun Zhang, Jun Xie, Jordan L. Boyd-Graber:
Automatic Song Translation for Tonal Languages. ACL (Findings) 2022: 729-743 - [c112]Yoshinari Fujinuma, Jordan L. Boyd-Graber, Katharina Kann:
Match the Script, Adapt if Multilingual: Analyzing the Effect of Multilingual Pretraining on Cross-lingual Transferability. ACL (1) 2022: 1500-1512 - [c111]Michelle Yuan, Patrick Xia, Chandler May, Benjamin Van Durme, Jordan L. Boyd-Graber:
Adapting Coreference Resolution Models through Active Learning. ACL (1) 2022: 7533-7549 - [c110]Chenglei Si, Chen Zhao, Sewon Min, Jordan L. Boyd-Graber:
Re-Examining Calibration: The Case of Question Answering. EMNLP (Findings) 2022: 2814-2829 - [c109]Wanrong He, Andrew Mao, Jordan L. Boyd-Graber:
Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain QA. EMNLP (Findings) 2022: 3627-3639 - [c108]HyoJung Han, Marine Carpuat, Jordan L. Boyd-Graber:
SimQA: Detecting Simultaneous MT Errors through Word-by-Word Question Answering. EMNLP 2022: 5598-5616 - [c107]Shi Feng, Jordan L. Boyd-Graber:
Learning to Explain Selectively: A Case Study on Question Answering. EMNLP 2022: 8372-8382 - [i47]Yoshinari Fujinuma, Jordan L. Boyd-Graber, Katharina Kann:
Match the Script, Adapt if Multilingual: Analyzing the Effect of Multilingual Pretraining on Cross-lingual Transferability. CoRR abs/2203.10753 (2022) - [i46]Fenfei Guo, Chen Zhang, Zhirui Zhang, Qixin He, Kejun Zhang, Jun Xie, Jordan L. Boyd-Graber:
Automatic Song Translation for Tonal Languages. CoRR abs/2203.13420 (2022) - [i45]Chenglei Si, Chen Zhao, Sewon Min, Jordan L. Boyd-Graber:
Revisiting Calibration for Question Answering. CoRR abs/2205.12507 (2022) - [i44]Saptarashmi Bandyopadhyay, Shraman Pal, Hao Zou, Abhranil Chandra, Jordan L. Boyd-Graber:
Improving Question Answering with Generation of NQ-like Questions. CoRR abs/2210.06599 (2022) - [i43]Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang, Jordan L. Boyd-Graber, Lijuan Wang:
Prompting GPT-3 To Be Reliable. CoRR abs/2210.09150 (2022) - [i42]Wanrong He, Andrew Mao, Jordan L. Boyd-Graber:
Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain Question Answering. CoRR abs/2212.03296 (2022) - 2021
- [c106]Pedro Rodriguez, Joe Barrow, Alexander Miserlis Hoyle, John P. Lalor, Robin Jia, Jordan L. Boyd-Graber:
Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards? ACL/IJCNLP (1) 2021: 4486-4503 - [c105]Denis Peskov, Viktor Hangya, Jordan L. Boyd-Graber, Alexander Fraser:
Adapting Entities across Languages and Cultures. EMNLP (Findings) 2021: 3725-3750 - [c104]Maharshi Gor, Kellie Webster, Jordan L. Boyd-Graber:
Toward Deconfounding the Effect of Entity Demographics for Question Answering Accuracy. EMNLP (1) 2021: 5457-5473 - [c103]Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III:
Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation. EMNLP (1) 2021: 9612-9622 - [c102]Chenglei Si, Chen Zhao, Jordan L. Boyd-Graber:
What's in a Name? Answer Equivalence For Open-Domain Question Answering. EMNLP (1) 2021: 9623-9629 - [c101]Pedro Rodriguez, Jordan L. Boyd-Graber:
Evaluation Paradigms in Question Answering. EMNLP (1) 2021: 9630-9642 - [c100]Julian Martin Eisenschlos, Bhuwan Dhingra, Jannis Bulian, Benjamin Börschinger, Jordan L. Boyd-Graber:
Fool Me Twice: Entailment from Wikipedia Gamification. NAACL-HLT 2021: 352-365 - [c99]Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III:
Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval. NAACL-HLT 2021: 4635-4641 - [c98]Alexander Miserlis Hoyle, Pranav Goel, Andrew Hian-Cheong, Denis Peskov, Jordan L. Boyd-Graber, Philip Resnik:
Is Automated Topic Model Evaluation Broken? The Incoherence of Coherence. NeurIPS 2021: 2018-2033 - [i41]Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick S. H. Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih:
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. CoRR abs/2101.00133 (2021) - [i40]Chen Zhao, Chenyan Xiong, Xin Qian, Jordan L. Boyd-Graber:
Complex Factoid Question Answering with a Free-Text Knowledge Graph. CoRR abs/2103.12876 (2021) - [i39]Julian Martin Eisenschlos, Bhuwan Dhingra, Jannis Bulian, Benjamin Börschinger, Jordan L. Boyd-Graber:
Fool Me Twice: Entailment from Wikipedia Gamification. CoRR abs/2104.04725 (2021) - [i38]Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III:
Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval. CoRR abs/2104.05883 (2021) - [i37]Maharshi Gor, Kellie Webster, Jordan L. Boyd-Graber:
Towards Deconfounding the Influence of Subject's Demographic Characteristics in Question Answering. CoRR abs/2104.07571 (2021) - [i36]Michelle Yuan, Patrick Xia, Benjamin Van Durme, Jordan L. Boyd-Graber:
Adaptive Active Learning for Coreference Resolution. CoRR abs/2104.07611 (2021) - [i35]Alexander Miserlis Hoyle, Pranav Goel, Denis Peskov, Andrew Hian-Cheong, Jordan L. Boyd-Graber, Philip Resnik:
Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence. CoRR abs/2107.02173 (2021) - [i34]Chenglei Si, Chen Zhao, Jordan L. Boyd-Graber:
What's in a Name? Answer Equivalence For Open-Domain Question Answering. CoRR abs/2109.05289 (2021) - [i33]Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III:
Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence Annotation. CoRR abs/2110.04889 (2021) - 2020
- [c97]Mozhi Zhang, Yoshinari Fujinuma, Jordan L. Boyd-Graber:
Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification. AAAI 2020: 9547-9554 - [c96]Mozhi Zhang, Yoshinari Fujinuma, Michael J. Paul, Jordan L. Boyd-Graber:
Why Overfitting Isn't Always Bad: Retrofitting Cross-Lingual Word Embeddings to Dictionaries. ACL 2020: 2214-2220 - [c95]Denis Peskov, Benny Cheng, Ahmed Elgohary, Joe Barrow, Cristian Danescu-Niculescu-Mizil, Jordan L. Boyd-Graber:
It Takes Two to Lie: One to Lie, and One to Listen. ACL 2020: 3811-3854 - [c94]Jordan L. Boyd-Graber, Benjamin Börschinger:
What Question Answering can Learn from Trivia Nerds. ACL 2020: 7422-7435 - [c93]Alison Smith-Renner, Ron Fan, Melissa Birchfield, Tongshuang Wu, Jordan L. Boyd-Graber, Daniel S. Weld, Leah Findlater:
No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML. CHI 2020: 1-13 - [c92]Wenyan Li, Alvin Grissom II, Jordan L. Boyd-Graber:
An Attentive Recurrent Model for Incremental Prediction of Sentence-final Verbs. EMNLP (Findings) 2020: 126-136 - [c91]Tianze Shi, Chen Zhao, Jordan L. Boyd-Graber, Hal Daumé III, Lillian Lee:
On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries. EMNLP (Findings) 2020: 1849-1864 - [c90]Michelle Yuan, Mozhi Zhang, Benjamin Van Durme, Leah Findlater, Jordan L. Boyd-Graber:
Interactive Refinement of Cross-Lingual Word Embeddings. EMNLP (1) 2020: 5984-5996 - [c89]Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber:
Cold-start Active Learning through Self-supervised Language Modeling. EMNLP (1) 2020: 7935-7948 - [c88]Alison Smith-Renner, Varun Kumar, Jordan L. Boyd-Graber, Kevin D. Seppi, Leah Findlater:
Digging into user control: perceptions of adherence and instability in transparent models. IUI 2020: 519-530 - [c87]Jordan L. Boyd-Graber, Fenfei Guo, Leah Findlater, Mohit Iyyer:
Which Evaluations Uncover Sense Representations that Actually Make Sense? LREC 2020: 1727-1738 - [c86]Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick S. H. Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih:
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. NeurIPS (Competition and Demos) 2020: 86-111 - [c85]Chen Zhao, Chenyan Xiong, Xin Qian, Jordan L. Boyd-Graber:
Complex Factoid Question Answering with a Free-Text Knowledge Graph. WWW 2020: 1205-1216 - [i32]Mozhi Zhang, Yoshinari Fujinuma, Michael J. Paul, Jordan L. Boyd-Graber:
Why Overfitting Isn't Always Bad: Retrofitting Cross-Lingual Word Embeddings to Dictionaries. CoRR abs/2005.00524 (2020) - [i31]Michelle Yuan, Hsuan-Tien Lin, Jordan L. Boyd-Graber:
Cold-start Active Learning through Self-supervised Language Modeling. CoRR abs/2010.09535 (2020) - [i30]Tianze Shi, Chen Zhao, Jordan L. Boyd-Graber, Hal Daumé III, Lillian Lee:
On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries. CoRR abs/2010.11246 (2020) - [i29]Francesco S. Varini, Jordan L. Boyd-Graber, Massimiliano Ciaramita, Markus Leippold:
ClimaText: A Dataset for Climate Change Topic Detection. CoRR abs/2012.00483 (2020) - [i28]Thomas Diggelmann, Jordan L. Boyd-Graber, Jannis Bulian, Massimiliano Ciaramita, Markus Leippold:
CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims. CoRR abs/2012.00614 (2020)
2010 – 2019
- 2019
- [j8]Eric Wallace, Pedro Rodriguez, Shi Feng, Ikuya Yamada, Jordan L. Boyd-Graber:
Trick Me If You Can: Human-in-the-loop Generation of Adversarial Question Answering Examples. Trans. Assoc. Comput. Linguistics 7: 387-401 (2019) - [c84]Jeffrey Lund, Piper Armstrong, Wilson Fearn, Stephen Cowley, Courtni Byun, Jordan L. Boyd-Graber, Kevin D. Seppi:
Automatic Evaluation of Local Topic Quality. ACL (1) 2019: 788-796 - [c83]Mozhi Zhang, Keyulu Xu, Ken-ichi Kawarabayashi, Stefanie Jegelka, Jordan L. Boyd-Graber:
Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization. ACL (1) 2019: 3180-3189 - [c82]Yoshinari Fujinuma, Jordan L. Boyd-Graber, Michael J. Paul:
A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity. ACL (1) 2019: 4952-4962 - [c81]Shi Feng, Eric Wallace, Jordan L. Boyd-Graber:
Misleading Failures of Partial-input Baselines. ACL (1) 2019: 5533-5538 - [c80]Varun Kumar, Alison Smith-Renner, Leah Findlater, Kevin D. Seppi, Jordan L. Boyd-Graber:
Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models. ACL (1) 2019: 6323-6330 - [c79]Weiwei Yang, Jordan L. Boyd-Graber, Philip Resnik:
A Multilingual Topic Model for Learning Weighted Topic Links Across Corpora with Low Comparability. EMNLP/IJCNLP (1) 2019: 1243-1248 - [c78]Ahmed Elgohary, Denis Peskov, Jordan L. Boyd-Graber:
Can You Unpack That? Learning to Rewrite Questions-in-Context. EMNLP/IJCNLP (1) 2019: 5917-5923 - [c77]Denis Peskov, Joe Barrow, Pedro Rodriguez, Graham Neubig, Jordan L. Boyd-Graber:
Mitigating Noisy Inputs for Question Answering. INTERSPEECH 2019: 789-793 - [c76]Shi Feng, Jordan L. Boyd-Graber:
What can AI do for me?: evaluating machine learning interpretations in cooperative play. IUI 2019: 229-239 - [i27]Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He, Jordan L. Boyd-Graber:
Quizbowl: The Case for Incremental Question Answering. CoRR abs/1904.04792 (2019) - [i26]Shi Feng, Eric Wallace, Jordan L. Boyd-Graber:
Misleading Failures of Partial-input Baselines. CoRR abs/1905.05778 (2019) - [i25]Varun Kumar, Alison Smith-Renner, Leah Findlater, Kevin D. Seppi, Jordan L. Boyd-Graber:
Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models. CoRR abs/1905.09864 (2019) - [i24]Jeffrey Lund, Piper Armstrong, Wilson Fearn, Stephen Cowley, Courtni Byun, Jordan L. Boyd-Graber, Kevin D. Seppi:
Automatic Evaluation of Local Topic Quality. CoRR abs/1905.13126 (2019) - [i23]Mozhi Zhang, Keyulu Xu, Ken-ichi Kawarabayashi, Stefanie Jegelka, Jordan L. Boyd-Graber:
Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization. CoRR abs/1906.01622 (2019) - [i22]Yoshinari Fujinuma, Jordan L. Boyd-Graber, Michael J. Paul:
A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity. CoRR abs/1906.01926 (2019) - [i21]Denis Peskov, Joe Barrow, Pedro Rodriguez, Graham Neubig, Jordan L. Boyd-Graber:
Mitigating Noisy Inputs for Question Answering. CoRR abs/1908.02914 (2019) - [i20]Jordan L. Boyd-Graber:
What Question Answering can Learn from Trivia Nerds. CoRR abs/1910.14464 (2019) - [i19]Michelle Yuan, Mozhi Zhang, Benjamin Van Durme, Leah Findlater, Jordan L. Boyd-Graber:
Interactive Refinement of Cross-Lingual Word Embeddings. CoRR abs/1911.03070 (2019) - [i18]Benjamin Börschinger, Jordan L. Boyd-Graber, Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Michelle Chen Huebscher, Wojciech Gajewski, Yannic Kilcher, Rodrigo Nogueira, Lierni Sestorain Saralegu:
Meta Answering for Machine Reading. CoRR abs/1911.04156 (2019) - 2018
- [c75]Eric Wallace, Jordan L. Boyd-Graber:
Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions. ACL (3) 2018: 127-133 - [c74]Craig Stewart, Nikolai Vogler, Junjie Hu, Jordan L. Boyd-Graber, Graham Neubig:
Automatic Estimation of Simultaneous Interpreter Performance. ACL (2) 2018: 662-666 - [c73]Paul Felt, Eric K. Ringger, Jordan L. Boyd-Graber, Kevin D. Seppi:
Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types. COLING 2018: 1694-1704 - [c72]Eric Wallace, Shi Feng, Jordan L. Boyd-Graber:
Interpreting Neural Networks with Nearest Neighbors. BlackboxNLP@EMNLP 2018: 136-144 - [c71]Ahmed Elgohary, Chen Zhao, Jordan L. Boyd-Graber:
A dataset and baselines for sequential open-domain question answering. EMNLP 2018: 1077-1083 - [c70]Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, Jordan L. Boyd-Graber:
Pathologies of Neural Models Make Interpretation Difficult. EMNLP 2018: 3719-3728 - [c69]Alison Smith, Varun Kumar, Jordan L. Boyd-Graber, Kevin D. Seppi, Leah Findlater:
Closing the Loop: User-Centered Design and Evaluation of a Human-in-the-Loop Topic Modeling System. IUI 2018: 293-304 - [c68]Varun Manjunatha, Mohit Iyyer, Jordan L. Boyd-Graber, Larry S. Davis:
Learning to Color from Language. NAACL-HLT (2) 2018: 764-769 - [c67]Shudong Hao, Jordan L. Boyd-Graber, Michael J. Paul:
Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation. NAACL-HLT 2018: 1090-1100 - [i17]Varun Manjunatha, Mohit Iyyer, Jordan L. Boyd-Graber, Larry S. Davis:
Learning to Color from Language. CoRR abs/1804.06026 (2018) - [i16]Shi Feng, Eric Wallace, Mohit Iyyer, Pedro Rodriguez, Alvin Grissom II, Jordan L. Boyd-Graber:
Right Answer for the Wrong Reason: Discovery and Mitigation. CoRR abs/1804.07781 (2018) - [i15]Fenfei Guo, Mohit Iyyer, Jordan L. Boyd-Graber:
Inducing and Embedding Senses with Scaled Gumbel Softmax. CoRR abs/1804.08077 (2018) - [i14]Shudong Hao, Jordan L. Boyd-Graber, Michael J. Paul:
Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation. CoRR abs/1804.10184 (2018) - [i13]Craig Stewart, Nikolai Vogler, Junjie Hu, Jordan L. Boyd-Graber, Graham Neubig:
Automatic Estimation of Simultaneous Interpreter Performance. CoRR abs/1805.04016 (2018) - [i12]Eric Wallace, Pedro Rodriguez, Shi Feng, Jordan L. Boyd-Graber:
Trick Me If You Can: Adversarial Writing of Trivia Challenge Questions. CoRR abs/1809.02701 (2018) - [i11]Eric Wallace, Shi Feng, Jordan L. Boyd-Graber:
Interpreting Neural Networks With Nearest Neighbors. CoRR abs/1809.02847 (2018) - [i10]Shi Feng, Jordan L. Boyd-Graber:
What can AI do for me: Evaluating Machine Learning Interpretations in Cooperative Play. CoRR abs/1810.09648 (2018) - [i9]Mozhi Zhang, Yoshinari Fujinuma, Jordan L. Boyd-Graber:
Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification. CoRR abs/1812.09617 (2018) - 2017
- [j7]Jordan L. Boyd-Graber,