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- affiliation: University of Massachusetts Amherst, USA
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2020 – today
- 2023
[c267]Haw-Shiuan Chang, Ruei-Yao Sun, Kathryn Ricci, Andrew McCallum:
Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling. ACL (1) 2023: 821-854- [c266]Raymond Zhang, Neha Nayak Kennard, Daniel Smith, Daniel A. McFarland, Andrew McCallum, Katherine Keith:
Causal Matching with Text Embeddings: A Case Study in Estimating the Causal Effects of Peer Review Policies. ACL (Findings) 2023: 1284-1297 - [c265]Haw-Shiuan Chang, Zonghai Yao, Alolika Gon, Hong Yu, Andrew McCallum:
Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond. ACL (Findings) 2023: 12707-12730 - [c264]Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew McCallum:
Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining. AISTATS 2023: 9308-9330 - [c263]Kumar Shridhar, Nicholas Monath, Raghuveer Thirukovalluru, Alessandro Stolfo, Manzil Zaheer, Andrew McCallum, Mrinmaya Sachan:
Longtonotes: OntoNotes with Longer Coreference Chains. EACL (Findings) 2023: 1398-1412 - [c262]Subendhu Rongali, Mukund Sridhar, Haidar Khan, Konstantine Arkoudas, Wael Hamza, Andrew McCallum:
Low-Resource Compositional Semantic Parsing with Concept Pretraining. EACL 2023: 1402-1411 - [c261]Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi:
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. ICLR 2023 - [c260]Nicholas Monath
, Manzil Zaheer, Andrew McCallum:
Online Level-wise Hierarchical Clustering. KDD 2023: 1733-1745 - [c259]Sheshera Mysore, Andrew McCallum, Hamed Zamani:
Large Language Model Augmented Narrative Driven Recommendations. RecSys 2023: 777-783 - [c258]Sheshera Mysore, Mahmood Jasim, Andrew McCallum, Hamed Zamani:
Editable User Profiles for Controllable Text Recommendations. SIGIR 2023: 993-1003 - [c257]Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi:
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. SustaiNLP 2023: 1-31 - [i119]Subendhu Rongali, Mukund Sridhar, Haidar Khan, Konstantine Arkoudas, Wael Hamza, Andrew McCallum:
Low-Resource Compositional Semantic Parsing with Concept Pretraining. CoRR abs/2301.09809 (2023) - [i118]Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew McCallum:
Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining. CoRR abs/2303.15311 (2023) - [i117]Sheshera Mysore, Mahmood Jasim, Andrew McCallum, Hamed Zamani:
Editable User Profiles for Controllable Text Recommendation. CoRR abs/2304.04250 (2023) - [i116]Nishant Yadav, Nicholas Monath, Manzil Zaheer, Andrew McCallum:
Adaptive Selection of Anchor Items for CUR-based k-NN search with Cross-Encoders. CoRR abs/2305.02996 (2023) - [i115]Haw-Shiuan Chang, Zonghai Yao, Alolika Gon, Hong Yu, Andrew McCallum:
Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond. CoRR abs/2305.12289 (2023) - [i114]Dung Thai, Dhruv Agarwal, Mudit Chaudhary, Rajarshi Das, Manzil Zaheer, Jay-Yoon Lee, Hannaneh Hajishirzi, Andrew McCallum:
Machine Reading Comprehension using Case-based Reasoning. CoRR abs/2305.14815 (2023) - [i113]Sheshera Mysore, Andrew McCallum, Hamed Zamani:
Large Language Model Augmented Narrative Driven Recommendations. CoRR abs/2306.02250 (2023) - [i112]Shib Sankar Dasgupta, Andrew McCallum, Steffen Rendle, Li Zhang:
Answering Compositional Queries with Set-Theoretic Embeddings. CoRR abs/2306.04133 (2023) - [i111]Ronald Seoh, Haw-Shiuan Chang, Andrew McCallum:
Encoding Multi-Domain Scientific Papers by Ensembling Multiple CLS Tokens. CoRR abs/2309.04333 (2023) - [i110]Haw-Shiuan Chang, Nikhil Agarwal, Andrew McCallum:
To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential Recommenders. CoRR abs/2310.14079 (2023) - [i109]Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, Kai Hui:
PaRaDe: Passage Ranking using Demonstrations with Large Language Models. CoRR abs/2310.14408 (2023) - [i108]Jiachen Zhao, Wenlong Zhao, Andrew Drozdov, Benjamin Rozonoyer, Md. Arafat Sultan, Jay-Yoon Lee, Mohit Iyyer, Andrew McCallum:
Multistage Collaborative Knowledge Distillation from Large Language Models. CoRR abs/2311.08640 (2023) - 2022
- [c256]Siddhartha Mishra, Nicholas Monath, Michael Boratko, Ariel Kobren, Andrew McCallum:
An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity. AAAI 2022: 7788-7796 - [c255]Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco:
Sublinear Time Approximation of Text Similarity Matrices. AAAI 2022: 8072-8080 - [c254]EunJeong Hwang, Jay-Yoon Lee, Tianyi Yang, Dhruvesh Patel, Dongxu Zhang, Andrew McCallum:
Event-Event Relation Extraction using Probabilistic Box Embedding. ACL (2) 2022: 235-244 - [c253]Shib Sankar Dasgupta, Michael Boratko, Siddhartha Mishra, Shriya Atmakuri, Dhruvesh Patel, Xiang Li, Andrew McCallum:
Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings. ACL (1) 2022: 2263-2276 - [c252]Haw-Shiuan Chang, Andrew McCallum:
Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions. ACL (1) 2022: 8048-8073 - [c251]Trapit Bansal, Salaheddin Alzubi, Tong Wang, Jay-Yoon Lee, Andrew McCallum:
Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-Learning. AutoML 2022: 19/1-18 - [c250]Kathryn Ricci, Haw-Shiuan Chang, Purujit Goyal, Andrew McCallum:
Unsupervised Partial Sentence Matching for Cited Text Identification. SDP@COLING 2022: 95-104 - [c249]Nishant Yadav, Nicholas Monath, Rico Angell, Manzil Zaheer, Andrew McCallum:
Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization. EMNLP 2022: 2171-2194 - [c248]Andrew Drozdov, Shufan Wang, Razieh Rahimi, Andrew McCallum, Hamed Zamani, Mohit Iyyer:
You can't pick your neighbors, or can you? When and How to Rely on Retrieval in the kNN-LM. EMNLP (Findings) 2022: 2997-3007 - [c247]Dhruvesh Patel, Pavitra Dangati, Jay-Yoon Lee, Michael Boratko, Andrew McCallum:
Modeling Label Space Interactions in Multi-label Classification using Box Embeddings. ICLR 2022 - [c246]Rico Angell, Nicholas Monath, Nishant Yadav, Andrew McCallum:
Interactive Correlation Clustering with Existential Cluster Constraints. ICML 2022: 703-716 - [c245]Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Manzil Zaheer, Hannaneh Hajishirzi, Robin Jia, Andrew McCallum:
Knowledge Base Question Answering by Case-based Reasoning over Subgraphs. ICML 2022: 4777-4793 - [c244]Dongxu Zhang, Sunil Mohan, Michaela Torkar, Andrew McCallum:
A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and Genes. LREC 2022: 1073-1082 - [c243]Jui Shah, Dongxu Zhang, Sam Brody, Andrew McCallum:
Enhanced Distant Supervision with State-Change Information for Relation Extraction. LREC 2022: 5573-5579 - [c242]Andrew Drozdov, Jiawei Zhou, Radu Florian, Andrew McCallum, Tahira Naseem, Yoon Kim, Ramón Fernandez Astudillo:
Inducing and Using Alignments for Transition-based AMR Parsing. NAACL-HLT 2022: 1086-1098 - [c241]Neha Nayak Kennard, Tim O'Gorman, Rajarshi Das, Akshay Sharma, Chhandak Bagchi, Matthew Clinton, Pranay Kumar Yelugam, Hamed Zamani, Andrew McCallum:
DISAPERE: A Dataset for Discourse Structure in Peer Review Discussions. NAACL-HLT 2022: 1234-1249 - [c240]Dhruv Agarwal, Rico Angell, Nicholas Monath, Andrew McCallum:
Entity Linking via Explicit Mention-Mention Coreference Modeling. NAACL-HLT 2022: 4644-4658 - [c239]Jay Yoon Lee, Dhruvesh Patel, Purujit Goyal, Wenlong Zhao, Zhiyang Xu, Andrew McCallum:
Structured Energy Network As a Loss. NeurIPS 2022 - [c238]Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum:
Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings. NeurIPS 2022 - [i107]Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Robin Jia, Manzil Zaheer, Hannaneh Hajishirzi, Andrew McCallum:
Knowledge Base Question Answering by Case-based Reasoning over Subgraphs. CoRR abs/2202.10610 (2022) - [i106]Dongxu Zhang, Sunil Mohan, Michaela Torkar, Andrew McCallum:
A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and Genes. CoRR abs/2204.06584 (2022) - [i105]Dung Thai, Srinivas Ravishankar, Ibrahim Abdelaziz, Mudit Chaudhary, Nandana Mihindukulasooriya, Tahira Naseem, Rajarshi Das, Pavan Kapanipathi, Achille Fokoue, Andrew McCallum:
CBR-iKB: A Case-Based Reasoning Approach for Question Answering over Incomplete Knowledge Bases. CoRR abs/2204.08554 (2022) - [i104]Andrew Drozdov, Jiawei Zhou, Radu Florian, Andrew McCallum, Tahira Naseem, Yoon Kim, Ramón Fernandez Astudillo:
Inducing and Using Alignments for Transition-based AMR Parsing. CoRR abs/2205.01464 (2022) - [i103]Hyeonsu B. Kang, Sheshera Mysore, Kevin Huang, Haw-Shiuan Chang, Thorben Prein, Andrew McCallum, Aniket Kittur, Elsa Olivetti:
Augmenting Scientific Creativity with Retrieval across Knowledge Domains. CoRR abs/2206.01328 (2022) - [i102]Kumar Shridhar, Nicholas Monath, Raghuveer Thirukovalluru, Alessandro Stolfo, Manzil Zaheer, Andrew McCallum, Mrinmaya Sachan:
Longtonotes: OntoNotes with Longer Coreference Chains. CoRR abs/2210.03650 (2022) - [i101]Haw-Shiuan Chang, Ruei-Yao Sun, Kathryn Ricci, Andrew McCallum:
Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling. CoRR abs/2210.05043 (2022) - [i100]Nishant Yadav, Nicholas Monath, Rico Angell, Manzil Zaheer, Andrew McCallum:
Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization. CoRR abs/2210.12579 (2022) - [i99]Andrew Drozdov, Shufan Wang, Razieh Rahimi, Andrew McCallum, Hamed Zamani, Mohit Iyyer:
You can't pick your neighbors, or can you? When and how to rely on retrieval in the kNN-LM. CoRR abs/2210.15859 (2022) - 2021
- [c237]Haw-Shiuan Chang, Amol Agrawal, Andrew McCallum:
Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications. AAAI 2021: 6956-6965 - [c236]Ahsaas Bajaj, Pavitra Dangati, Kalpesh Krishna, Pradhiksha Ashok Kumar, Rheeya Uppaal, Bradford Windsor, Eliot Brenner, Dominic Dotterrer, Rajarshi Das, Andrew McCallum:
Long Document Summarization in a Low Resource Setting using Pretrained Language Models. ACL (student) 2021: 71-80 - [c235]Nicholas FitzGerald, Daniel M. Bikel, Jan A. Botha, Daniel Gillick, Tom Kwiatkowski, Andrew McCallum:
MOLEMAN: Mention-Only Linking of Entities with a Mention Annotation Network. ACL/IJCNLP (2) 2021: 278-285 - [c234]Yasumasa Onoe, Michael Boratko, Andrew McCallum, Greg Durrett:
Modeling Fine-Grained Entity Types with Box Embeddings. ACL/IJCNLP (1) 2021: 2051-2064 - [c233]Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, Manzil Zaheer, Mrinmaya Sachan, Andrew McCallum:
Scaling Within Document Coreference to Long Texts. ACL/IJCNLP (Findings) 2021: 3921-3931 - [c232]Sumanta Bhattacharyya, Amirmohammad Rooshenas, Subhajit Naskar, Simeng Sun, Mohit Iyyer, Andrew McCallum:
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models. ACL/IJCNLP (1) 2021: 4528-4537 - [c231]Robert L. Logan IV, Andrew McCallum, Sameer Singh, Daniel M. Bikel:
Benchmarking Scalable Methods for Streaming Cross Document Entity Coreference. ACL/IJCNLP (1) 2021: 4717-4731 - [c230]Sebastian Macaluso, Craig S. Greenberg, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum:
Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering. AISTATS 2021: 2467-2475 - [c229]Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum:
DAG-Structured Clustering by Nearest Neighbors. AISTATS 2021: 2854-2862 - [c228]Sunil Mohan, Rico Angell, Nicholas Monath, Andrew McCallum:
Low resource recognition and linking of biomedical concepts from a large ontology. BCB 2021: 54:1-54:10 - [c227]Rohan Paul, Haw-Shiuan Chang, Andrew McCallum:
Multi-facet Universal Schema. EACL 2021: 909-919 - [c226]Haw-Shiuan Chang, Jiaming Yuan, Mohit Iyyer, Andrew McCallum:
Changing the Mind of Transformers for Topically-Controllable Language Generation. EACL 2021: 2601-2611 - [c225]Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum:
Box Embeddings: An open-source library for representation learning using geometric structures. EMNLP (Demos) 2021: 203-211 - [c224]Tim O'Gorman, Zach Jensen, Sheshera Mysore, Kevin Huang, Rubayyat Mahbub, Elsa Olivetti, Andrew McCallum:
MS-Mentions: Consistently Annotating Entity Mentions in Materials Science Procedural Text. EMNLP (1) 2021: 1337-1352 - [c223]Zhiyang Xu, Andrew Drozdov, Jay-Yoon Lee, Tim O'Gorman, Subendhu Rongali, Dylan Finkbeiner, Shilpa Suresh, Mohit Iyyer, Andrew McCallum:
Improved Latent Tree Induction with Distant Supervision via Span Constraints. EMNLP (1) 2021: 4818-4831 - [c222]Trapit Bansal, Karthick Prasad Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum:
Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP. EMNLP (1) 2021: 5812-5824 - [c221]Rajarshi Das, Manzil Zaheer, Dung Thai, Ameya Godbole, Ethan Perez, Jay Yoon Lee, Lizhen Tan, Lazaros Polymenakos, Andrew McCallum:
Case-based Reasoning for Natural Language Queries over Knowledge Bases. EMNLP (1) 2021: 9594-9611 - [c220]Nicholas Monath, Kumar Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu:
Scalable Hierarchical Agglomerative Clustering. KDD 2021: 1245-1255 - [c219]Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum:
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. NAACL-HLT 2021: 882-893 - [c218]Rico Angell, Nicholas Monath, Sunil Mohan, Nishant Yadav, Andrew McCallum:
Clustering-based Inference for Biomedical Entity Linking. NAACL-HLT 2021: 2598-2608 - [c217]Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L. Clarkson, Andrew McCallum:
Capacity and Bias of Learned Geometric Embeddings for Directed Graphs. NeurIPS 2021: 16423-16436 - [c216]Sheshera Mysore, Tim O'Gorman, Andrew McCallum, Hamed Zamani:
CSFCube - A Test Collection of Computer Science Research Articles for Faceted Query by Example. NeurIPS Datasets and Benchmarks 2021 - [c215]Raghuveer Thirukovalluru, Mukund Sridhar, Dung Thai, Shruti Chanumolu, Nicholas Monath, Sankaranarayanan Ananthakrishnan, Andrew McCallum:
Knowledge Informed Semantic Parsing for Conversational Question Answering. RepL4NLP@ACL-IJCNLP 2021: 231-240 - [c214]Dung Thai, Raghuveer Thirukovalluru, Trapit Bansal, Andrew McCallum:
Simultaneously Self-Attending to Text and Entities for Knowledge-Informed Text Representations. RepL4NLP@ACL-IJCNLP 2021: 241-247 - [c213]Shib Sankar Dasgupta, Xiang Lorraine Li, Michael Boratko, Dongxu Zhang, Andrew McCallum:
Box-To-Box Transformations for Modeling Joint Hierarchies. RepL4NLP@ACL-IJCNLP 2021: 277-288 - [c212]Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum:
Exact and approximate hierarchical clustering using A. UAI 2021: 2061-2071 - [c211]Michael Boratko, Javier Burroni, Shib Sankar Dasgupta, Andrew McCallum:
Min/max stability and box distributions. UAI 2021: 2146-2155 - [e4]Danqi Chen, Jonathan Berant, Andrew McCallum, Sameer Singh:
3rd Conference on Automated Knowledge Base Construction, AKBC 2021, Virtual, October 4-8, 2021. 2021 [contents] - [i98]Sunil Mohan, Rico Angell, Nicholas Monath, Andrew McCallum:
Low Resource Recognition and Linking of Biomedical Concepts from a Large Ontology. CoRR abs/2101.10587 (2021) - [i97]Ahsaas Bajaj, Pavitra Dangati, Kalpesh Krishna, Pradhiksha Ashok Kumar, Rheeya Uppaal, Bradford Windsor, Eliot Brenner, Dominic Dotterrer, Rajarshi Das, Andrew McCallum:
Long Document Summarization in a Low Resource Setting using Pretrained Language Models. CoRR abs/2103.00751 (2021) - [i96]Sheshera Mysore, Tim O'Gorman, Andrew McCallum, Hamed Zamani:
CSFCube - A Test Collection of Computer Science Research Articles for Faceted Query by Example. CoRR abs/2103.12906 (2021) - [i95]Haw-Shiuan Chang, Amol Agrawal, Andrew McCallum:
Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications. CoRR abs/2103.15330 (2021) - [i94]Haw-Shiuan Chang, Jiaming Yuan, Mohit Iyyer, Andrew McCallum:
Changing the Mind of Transformers for Topically-Controllable Language Generation. CoRR abs/2103.15335 (2021) - [i93]Rohan Paul, Haw-Shiuan Chang, Andrew McCallum:
Multi-facet Universal Schema. CoRR abs/2103.15339 (2021) - [i92]Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum:
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. CoRR abs/2104.04597 (2021) - [i91]Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum:
Exact and Approximate Hierarchical Clustering Using A. CoRR abs/2104.07061 (2021) - [i90]Rajarshi Das, Manzil Zaheer, Dung Thai, Ameya Godbole, Ethan Perez, Jay-Yoon Lee, Lizhen Tan, Lazaros Polymenakos, Andrew McCallum:
Case-based Reasoning for Natural Language Queries over Knowledge Bases. CoRR abs/2104.08762 (2021) - [i89]Nicholas FitzGerald, Jan A. Botha, Daniel Gillick, Daniel M. Bikel, Tom Kwiatkowski, Andrew McCallum:
MOLEMAN: Mention-Only Linking of Entities with a Mention Annotation Network. CoRR abs/2106.07352 (2021) - [i88]Shib Sankar Dasgupta, Michael Boratko, Shriya Atmakuri, Xiang Lorraine Li, Dhruvesh Patel, Andrew McCallum:
Word2Box: Learning Word Representation Using Box Embeddings. CoRR abs/2106.14361 (2021) - [i87]Dhruv Agarwal, Rico Angell, Nicholas Monath, Andrew McCallum:
Entity Linking and Discovery via Arborescence-based Supervised Clustering. CoRR abs/2109.01242 (2021) - [i86]Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum:
Box Embeddings: An open-source library for representation learning using geometric structures. CoRR abs/2109.04997 (2021) - [i85]Zhiyang Xu, Andrew Drozdov, Jay-Yoon Lee, Tim O'Gorman, Subendhu Rongali, Dylan Finkbeiner, Shilpa Suresh, Mohit Iyyer, Andrew McCallum:
Improved Latent Tree Induction with Distant Supervision via Span Constraints. CoRR abs/2109.05112 (2021) - [i84]Neha Nayak Kennard, Tim O'Gorman, Akshay Sharma, Chhandak Bagchi, Matthew Clinton, Pranay Kumar Yelugam, Rajarshi Das, Hamed Zamani, Andrew McCallum:
A Dataset for Discourse Structure in Peer Review Discussions. CoRR abs/2110.08520 (2021) - [i83]Trapit Bansal, Karthick Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum:
Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP. CoRR abs/2111.01322 (2021) - [i82]Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco:
Sublinear Time Approximation of Text Similarity Matrices. CoRR abs/2112.09631 (2021) - 2020
- [j21]Edward Kim, Zach Jensen, Alexander van Grootel, Kevin Huang, Matthew Staib, Sheshera Mysore, Haw-Shiuan Chang, Emma Strubell, Andrew McCallum, Stefanie Jegelka, Elsa Olivetti:
Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks. J. Chem. Inf. Model. 60(3): 1194-1201 (2020) - [j20]Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, Andrew McCallum:
Using error decay prediction to overcome practical issues of deep active learning for named entity recognition. Mach. Learn. 109(9-10): 1749-1778 (2020) - [c210]Trapit Bansal, Patrick Verga, Neha Choudhary, Andrew McCallum:
Simultaneously Linking Entities and Extracting Relations from Biomedical Text without Mention-Level Supervision. AAAI 2020: 7407-7414 - [c209]Emma Strubell, Ananya Ganesh, Andrew McCallum:
Energy and Policy Considerations for Modern Deep Learning Research. AAAI 2020: 13693-13696 - [c208]Rajarshi Das, Ameya Godbole, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum:
A Simple Approach to Case-Based Reasoning in Knowledge Bases. AKBC 2020 - [c207]Dhruvesh Patel, Shib Sankar Dasgupta, Michael Boratko, Xiang Li, Luke Vilnis, Andrew McCallum:
Representing Joint Hierarchies with Box Embeddings. AKBC 2020 - [c206]Derek Tam, Nicholas Monath, Ari Kobren, Andrew McCallum:
Predicting Institution Hierarchies with Set-based Models. AKBC 2020 - [c205]Dung Thai, Zhiyang Xu, Nicholas Monath, Boris Veytsman, Andrew McCallum:
Using BibTeX to Automatically Generate Labeled Data for Citation Field Extraction. AKBC 2020 - [c204]Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li, Trapit Bansal, Andrew McCallum, Ivana Williams, Ana-Maria Istrate:
Unsupervised Pre-training for Biomedical Question Answering. CLEF (Working Notes) 2020 - [c203]Trapit Bansal, Rishikesh Jha, Andrew McCallum:
Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks. COLING 2020: 5108-5123 - [c202]Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum:
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks. EMNLP (1) 2020: 522-534 - [c201]Michael Boratko, Xiang Li, Tim O'Gorman, Rajarshi Das, Dan Le, Andrew McCallum:
ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning. EMNLP (1) 2020: 1122-1136 - [c200]Daivik Swarup, Ahsaas Bajaj, Sheshera Mysore, Tim O'Gorman, Rajarshi Das, Andrew McCallum:
An Instance Level Approach for Shallow Semantic Parsing in Scientific Procedural Text. EMNLP (Findings) 2020: 3010-3017 - [c199]Rajarshi Das, Ameya Godbole, Nicholas Monath, Manzil Zaheer, Andrew McCallum:
Probabilistic Case-based Reasoning in Knowledge Bases. EMNLP (Findings) 2020: 4752-4765 - [c198]Andrew Drozdov, Subendhu Rongali, Yi-Pei Chen, Tim O'Gorman, Mohit Iyyer, Andrew McCallum:
Unsupervised Parsing with S-DIORA: Single Tree Encoding for Deep Inside-Outside Recursive Autoencoders. EMNLP (1) 2020: 4832-4845 - [c197]Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang,