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Andrew McCallum
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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
,