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2020 – today
- 2024
[c34]Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Raghavi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Evan Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo:
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. ACL (1) 2024: 15725-15788- [c33]Dirk Groeneveld, Iz Beltagy, Evan Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi:
OLMo: Accelerating the Science of Language Models. ACL (1) 2024: 15789-15809 - [c32]Rabeeh Karimi Mahabadi, Hamish Ivison, Jaesung Tae, James Henderson, Iz Beltagy, Matthew E. Peters, Arman Cohan:
TESS: Text-to-Text Self-Conditioned Simplex Diffusion. EACL (1) 2024: 2347-2361 - [i35]Luca Soldaini, Rodney Kinney, Akshita Bhagia
, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Raghavi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo:
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. CoRR abs/2402.00159 (2024) - [i34]Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi:
OLMo: Accelerating the Science of Language Models. CoRR abs/2402.00838 (2024) - 2023
- [c31]Avi Caciularu, Matthew E. Peters, Jacob Goldberger, Ido Dagan, Arman Cohan:
Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering. ACL (1) 2023: 1970-1989 - [c30]Qinyuan Ye, Iz Beltagy, Matthew E. Peters, Xiang Ren, Hannaneh Hajishirzi:
FiD-ICL: A Fusion-in-Decoder Approach for Efficient In-Context Learning. ACL (1) 2023: 8158-8185 - [c29]Hamish Ivison, Akshita Bhagia, Yizhong Wang, Hannaneh Hajishirzi, Matthew E. Peters:
HINT: Hypernetwork Instruction Tuning for Efficient Zero- and Few-Shot Generalisation. ACL (1) 2023: 11272-11288 - [c28]Alexandra Chronopoulou, Matthew E. Peters, Alexander Fraser, Jesse Dodge:
AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models. EACL (Findings) 2023: 2009-2018 - [i33]Alexandra Chronopoulou, Matthew E. Peters, Alexander Fraser, Jesse Dodge:
AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models. CoRR abs/2302.07027 (2023) - [i32]Rabeeh Karimi Mahabadi, Jaesung Tae, Hamish Ivison, James Henderson, Iz Beltagy, Matthew E. Peters, Arman Cohan:
TESS: Text-to-Text Self-Conditioned Simplex Diffusion. CoRR abs/2305.08379 (2023) - [i31]Avi Caciularu, Matthew E. Peters, Jacob Goldberger, Ido Dagan, Arman Cohan:
Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering. CoRR abs/2305.15387 (2023) - [i30]Hao Peng, Qingqing Cao, Jesse Dodge, Matthew E. Peters, Jared Fernandez, Tom Sherborne, Kyle Lo, Sam Skjonsberg, Emma Strubell, Darrell Plessas, Iz Beltagy, Evan Pete Walsh, Noah A. Smith, Hannaneh Hajishirzi:
Efficiency Pentathlon: A Standardized Arena for Efficiency Evaluation. CoRR abs/2307.09701 (2023) - [i29]Oliver Watt-Meyer, Gideon Dresdner, Jeremy McGibbon, Spencer K. Clark, Brian Henn, James Duncan, Noah D. Brenowitz, Karthik Kashinath, Michael S. Pritchard, Boris Bonev, Matthew E. Peters, Christopher S. Bretherton:
ACE: A fast, skillful learned global atmospheric model for climate prediction. CoRR abs/2310.02074 (2023) - [i28]Hamish Ivison, Yizhong Wang, Valentina Pyatkin, Nathan Lambert, Matthew E. Peters, Pradeep Dasigi, Joel Jang, David Wadden, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi:
Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2. CoRR abs/2311.10702 (2023) - 2022
- [c27]Nishant Subramani, Nivedita Suresh, Matthew E. Peters:
Extracting Latent Steering Vectors from Pretrained Language Models. ACL (Findings) 2022: 566-581 - [c26]Alexis Ross, Tongshuang Wu, Hao Peng, Matthew E. Peters, Matt Gardner:
Tailor: Generating and Perturbing Text with Semantic Controls. ACL (1) 2022: 3194-3213 - [c25]Hamish Ivison, Matthew E. Peters:
Hyperdecoders: Instance-specific decoders for multi-task NLP. EMNLP (Findings) 2022: 1715-1730 - [c24]Akari Asai, Mohammadreza Salehi, Matthew E. Peters, Hannaneh Hajishirzi:
ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts. EMNLP 2022: 6655-6672 - [c23]Alexis Ross, Matthew E. Peters, Ana Marasovic:
Does Self-Rationalization Improve Robustness to Spurious Correlations? EMNLP 2022: 7403-7416 - [c22]Sheng Shen, Pete Walsh, Kurt Keutzer, Jesse Dodge, Matthew E. Peters, Iz Beltagy:
Staged Training for Transformer Language Models. ICML 2022: 19893-19908 - [c21]Ahmed Alshareef, Aaron Carass, Andrew K. Knutsen, Kshitiz Upadhyay, Matthew E. Peters, K. T. Ramesh, Jerry L. Prince:
Investigating the effect of ventricle size on brain deformation using computational models. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2022 - [c20]Ana Marasovic, Iz Beltagy, Doug Downey, Matthew E. Peters:
Few-Shot Self-Rationalization with Natural Language Prompts. NAACL-HLT (Findings) 2022: 410-424 - [c19]Alexandra Chronopoulou, Matthew E. Peters, Jesse Dodge:
Efficient Hierarchical Domain Adaptation for Pretrained Language Models. NAACL-HLT 2022: 1336-1351 - [i27]Sheng Shen, Pete Walsh, Kurt Keutzer, Jesse Dodge, Matthew E. Peters, Iz Beltagy:
Staged Training for Transformer Language Models. CoRR abs/2203.06211 (2022) - [i26]Hamish Ivison, Matthew E. Peters:
Hyperdecoders: Instance-specific decoders for multi-task NLP. CoRR abs/2203.08304 (2022) - [i25]Nishant Subramani, Nivedita Suresh, Matthew E. Peters:
Extracting Latent Steering Vectors from Pretrained Language Models. CoRR abs/2205.05124 (2022) - [i24]Akari Asai, Mohammadreza Salehi, Matthew E. Peters, Hannaneh Hajishirzi:
Attentional Mixtures of Soft Prompt Tuning for Parameter-efficient Multi-task Knowledge Sharing. CoRR abs/2205.11961 (2022) - [i23]Alexis Ross, Matthew E. Peters, Ana Marasovic:
Does Self-Rationalization Improve Robustness to Spurious Correlations? CoRR abs/2210.13575 (2022) - [i22]Hamish Ivison, Akshita Bhagia, Yizhong Wang, Hannaneh Hajishirzi, Matthew E. Peters:
HINT: Hypernetwork Instruction Tuning for Efficient Zero-Shot Generalisation. CoRR abs/2212.10315 (2022) - 2021
- [c18]Rowan Zellers, Ari Holtzman, Matthew E. Peters, Roozbeh Mottaghi, Aniruddha Kembhavi, Ali Farhadi, Yejin Choi:
PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World. ACL/IJCNLP (1) 2021: 2040-2050 - [c17]Alexis Ross, Ana Marasovic, Matthew E. Peters:
Explaining NLP Models via Minimal Contrastive Editing (MiCE). ACL/IJCNLP (Findings) 2021: 3840-3852 - [c16]Matt Gardner, William Merrill, Jesse Dodge, Matthew E. Peters, Alexis Ross, Sameer Singh, Noah A. Smith:
Competency Problems: On Finding and Removing Artifacts in Language Data. EMNLP (1) 2021: 1801-1813 - [c15]Avi Caciularu, Arman Cohan, Iz Beltagy, Matthew E. Peters, Arie Cattan, Ido Dagan:
CDLM: Cross-Document Language Modeling. EMNLP (Findings) 2021: 2648-2662 - [i21]Avi Caciularu, Arman Cohan, Iz Beltagy, Matthew E. Peters, Arie Cattan, Ido Dagan:
Cross-Document Language Modeling. CoRR abs/2101.00406 (2021) - [i20]Matt Gardner, William Merrill, Jesse Dodge, Matthew E. Peters, Alexis Ross, Sameer Singh, Noah A. Smith:
Competency Problems: On Finding and Removing Artifacts in Language Data. CoRR abs/2104.08646 (2021) - [i19]Rowan Zellers, Ari Holtzman, Matthew E. Peters, Roozbeh Mottaghi, Aniruddha Kembhavi, Ali Farhadi, Yejin Choi:
PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World. CoRR abs/2106.00188 (2021) - [i18]Alexis Ross, Tongshuang Wu, Hao Peng, Matthew E. Peters, Matt Gardner:
Tailor: Generating and Perturbing Text with Semantic Controls. CoRR abs/2107.07150 (2021) - [i17]Ana Marasovic, Iz Beltagy, Doug Downey, Matthew E. Peters:
Few-Shot Self-Rationalization with Natural Language Prompts. CoRR abs/2111.08284 (2021) - [i16]Alexandra Chronopoulou, Matthew E. Peters, Jesse Dodge:
Efficient Hierarchical Domain Adaptation for Pretrained Language Models. CoRR abs/2112.08786 (2021) - 2020
- [c14]Orion Weller, Nicholas Lourie, Matt Gardner, Matthew E. Peters:
Learning from Task Descriptions. EMNLP (1) 2020: 1361-1375 - [c13]Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, Yejin Choi:
Adversarial Filters of Dataset Biases. ICML 2020: 1078-1088 - [i15]Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, Yejin Choi:
Adversarial Filters of Dataset Biases. CoRR abs/2002.04108 (2020) - [i14]Iz Beltagy, Matthew E. Peters, Arman Cohan:
Longformer: The Long-Document Transformer. CoRR abs/2004.05150 (2020) - [i13]Orion Weller, Nicholas Lourie, Matt Gardner, Matthew E. Peters:
Learning from Task Descriptions. CoRR abs/2011.08115 (2020) - [i12]Alexis Ross, Ana Marasovic, Matthew E. Peters:
Explaining NLP Models via Minimal Contrastive Editing (MiCE). CoRR abs/2012.13985 (2020)
2010 – 2019
- 2019
- [c12]Robert L. Logan IV, Nelson F. Liu, Matthew E. Peters, Matt Gardner, Sameer Singh:
Barack's Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling. ACL (1) 2019: 5962-5971 - [c11]Matthew E. Peters, Mark Neumann, Robert L. Logan IV, Roy Schwartz, Vidur Joshi, Sameer Singh, Noah A. Smith:
Knowledge Enhanced Contextual Word Representations. EMNLP/IJCNLP (1) 2019: 43-54 - [c10]Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, Thomas Wolf:
Transfer Learning in Natural Language Processing. NAACL-HLT (Tutorial Abstracts) 2019: 15-18 - [c9]Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, Noah A. Smith:
Linguistic Knowledge and Transferability of Contextual Representations. NAACL-HLT (1) 2019: 1073-1094 - [c8]Matthew E. Peters, Sebastian Ruder, Noah A. Smith:
To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks. RepL4NLP@ACL 2019: 7-14 - [i11]Matthew E. Peters, Sebastian Ruder, Noah A. Smith:
To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks. CoRR abs/1903.05987 (2019) - [i10]Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, Noah A. Smith:
Linguistic Knowledge and Transferability of Contextual Representations. CoRR abs/1903.08855 (2019) - [i9]Robert L. Logan IV, Nelson F. Liu, Matthew E. Peters, Matt Gardner, Sameer Singh:
Barack's Wife Hillary: Using Knowledge-Graphs for Fact-Aware Language Modeling. CoRR abs/1906.07241 (2019) - [i8]Swabha Swayamdipta, Matthew E. Peters, Brendan Roof, Chris Dyer, Noah A. Smith:
Shallow Syntax in Deep Water. CoRR abs/1908.11047 (2019) - [i7]Matthew E. Peters, Mark Neumann, Robert L. Logan IV, Roy Schwartz, Vidur Joshi, Sameer Singh, Noah A. Smith:
Knowledge Enhanced Contextual Word Representations. CoRR abs/1909.04164 (2019) - 2018
- [c7]Vidur Joshi, Matthew E. Peters, Mark Hopkins:
Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples. ACL (1) 2018: 1190-1199 - [c6]Matthew E. Peters, Mark Neumann, Luke Zettlemoyer, Wen-tau Yih:
Dissecting Contextual Word Embeddings: Architecture and Representation. EMNLP 2018: 1499-1509 - [c5]Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, Iz Beltagy, Miles Crawford, Doug Downey, Jason Dunkelberger, Ahmed Elgohary, Sergey Feldman, Vu Ha, Rodney Kinney, Sebastian Kohlmeier, Kyle Lo, Tyler Murray, Hsu-Han Ooi, Matthew E. Peters, Joanna Power, Sam Skjonsberg, Lucy Lu Wang, Chris Wilhelm, Zheng Yuan, Madeleine van Zuylen, Oren Etzioni:
Construction of the Literature Graph in Semantic Scholar. NAACL-HLT (3) 2018: 84-91 - [c4]Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, Luke Zettlemoyer:
Deep Contextualized Word Representations. NAACL-HLT 2018: 2227-2237 - [i6]Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, Luke Zettlemoyer:
Deep contextualized word representations. CoRR abs/1802.05365 (2018) - [i5]Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson F. Liu, Matthew E. Peters, Michael Schmitz, Luke Zettlemoyer:
AllenNLP: A Deep Semantic Natural Language Processing Platform. CoRR abs/1803.07640 (2018) - [i4]Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, Iz Beltagy, Miles Crawford, Doug Downey, Jason Dunkelberger, Ahmed Elgohary, Sergey Feldman, Vu Ha, Rodney Kinney, Sebastian Kohlmeier, Kyle Lo, Tyler Murray, Hsu-Han Ooi, Matthew E. Peters, Joanna Power, Sam Skjonsberg, Lucy Lu Wang, Chris Wilhelm, Zheng Yuan, Madeleine van Zuylen, Oren Etzioni:
Construction of the Literature Graph in Semantic Scholar. CoRR abs/1805.02262 (2018) - [i3]Vidur Joshi, Matthew E. Peters, Mark Hopkins:
Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples. CoRR abs/1805.06556 (2018) - [i2]Matthew E. Peters, Mark Neumann, Luke Zettlemoyer, Wen-tau Yih:
Dissecting Contextual Word Embeddings: Architecture and Representation. CoRR abs/1808.08949 (2018) - 2017
- [c3]Matthew E. Peters, Waleed Ammar, Chandra Bhagavatula, Russell Power:
Semi-supervised sequence tagging with bidirectional language models. ACL (1) 2017: 1756-1765 - [c2]Waleed Ammar, Matthew E. Peters, Chandra Bhagavatula, Russell Power:
The AI2 system at SemEval-2017 Task 10 (ScienceIE): semi-supervised end-to-end entity and relation extraction. SemEval@ACL 2017: 592-596 - [i1]Matthew E. Peters, Waleed Ammar, Chandra Bhagavatula, Russell Power:
Semi-supervised sequence tagging with bidirectional language models. CoRR abs/1705.00108 (2017) - 2013
- [c1]Matthew E. Peters, Dan Lecocq:
Content extraction using diverse feature sets. WWW (Companion Volume) 2013: 89-90
2000 – 2009
- 2007
- [j2]Matthew E. Peters, Donald D. Blankenship, Diana E. Smith, John W. Holt, Scott D. Kempf:
The Distribution and Classification of Bottom Crevasses From Radar Sounding of a Large Tabular Iceberg. IEEE Geosci. Remote. Sens. Lett. 4(1): 142-146 (2007) - [j1]Matthew E. Peters, Donald D. Blankenship, Sasha P. Carter, Scott D. Kempf, Duncan A. Young, John W. Holt:
Along-Track Focusing of Airborne Radar Sounding Data From West Antarctica for Improving Basal Reflection Analysis and Layer Detection. IEEE Trans. Geosci. Remote. Sens. 45(9): 2725-2736 (2007)
Coauthor Index
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last updated on 2024-10-07 22:07 CEST by the dblp team
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