Methods for Domain-Independent Information Extraction from the Web: An Experimental Comparison. - Oren Etzioni; Michael J. Cafarella; Doug Downey; Ana-Maria Popescu; Tal Shaked; Stephen Soderland; Daniel S. Weld; Alexander Yates (AAAI, 2004)

Web-scale information extraction in knowitall: (preliminary results). - Oren Etzioni; Michael J. Cafarella; Doug Downey; Stanley Kok; Ana-Maria Popescu; Tal Shaked; Stephen Soderland; Daniel S. Weld; Alexander Yates (WWW, 2004)

A Probabilistic Model of Redundancy in Information Extraction. - Doug Downey; Oren Etzioni; Stephen Soderland (IJCAI, 2005)

KnowItNow: Fast, Scalable Information Extraction from the Web. - Michael J. Cafarella; Doug Downey; Stephen Soderland; Oren Etzioni (HLT/EMNLP, 2005)

Unsupervised named-entity extraction from the Web: An experimental study. - Oren Etzioni; Michael J. Cafarella; Doug Downey; Ana-Maria Popescu; Tal Shaked; Stephen Soderland; Daniel S. Weld; Alexander Yates (Artif. Intell., 2005)

Sparse Information Extraction: Unsupervised Language Models to the Rescue. - Doug Downey; Stefan Schoenmackers; Oren Etzioni (ACL, 2007)

Locating Complex Named Entities in Web Text. - Doug Downey; Matthew Broadhead; Oren Etzioni (IJCAI, 2007)

Models of Searching and Browsing: Languages, Studies, and Application. - Doug Downey; Susan T. Dumais; Eric Horvitz (IJCAI, 2007)

Heads and tails: studies of web search with common and rare queries. - Doug Downey; Susan T. Dumais; Eric Horvitz (SIGIR, 2007)

Understanding the relationship between searchers' queries and information goals. - Doug Downey; Susan T. Dumais; Daniel J. Liebling; Eric Horvitz (CIKM, 2008)

It's a Contradiction - no, it's not: A Case Study using Functional Relations. - Alan Ritter; Stephen Soderland; Doug Downey; Oren Etzioni (EMNLP, 2008)

Look Ma, No Hands: Analyzing the Monotonic Feature Abstraction for Text Classification. - Doug Downey; Oren Etzioni (NIPS, 2008)

Improved Extraction Assessment through Better Language Models. - Arun Ahuja; Doug Downey (HLT-NAACL, 2010)

Analysis of a probabilistic model of redundancy in unsupervised information extraction. - Doug Downey; Oren Etzioni; Stephen Soderland (Artif. Intell., 2010)

Local and Global Algorithms for Disambiguation to Wikipedia. - Lev-Arie Ratinov; Dan Roth 001; Doug Downey; Mike Anderson (ACL, 2011)

Language Models as Representations for Weakly Supervised NLP Tasks. - Fei Huang 008; Alexander Yates; Arun Ahuja; Doug Downey (CoNLL, 2011)

Explanatory semantic relatedness and explicit spatialization for exploratory search. - Brent J. Hecht; Samuel Carton; Mahmood Quaderi; Johannes Schöning; Martin Raubal; Darren Gergle; Doug Downey (SIGIR, 2012)

Sentiment identification by incorporating syntax, semantics and context information. - Kunpeng Zhang 001; Yusheng Xie; Yu Cheng 001; Daniel Honbo; Doug Downey; Ankit Agrawal 001; Wei-keng Liao; Alok N. Choudhary (SIGIR, 2012)

Scaling Semi-supervised Naive Bayes with Feature Marginals. - Michael Lucas; Doug Downey (ACL (1), 2013)

A probabilistic graphical model for brand reputation assessment in social networks. - Kunpeng Zhang 001; Doug Downey; Zhengzhang Chen; Yusheng Xie; Yu Cheng 001; Ankit Agrawal 001; Wei-keng Liao; Alok N. Choudhary (ASONAM, 2013)

Using natural language to integrate, evaluate, and optimize extracted knowledge bases. - Doug Downey; Chandra Sekhar Bhagavatula; Alexander Yates (AKBC@CIKM, 2013)

Methods for exploring and mining tables on Wikipedia. - Chandra Sekhar Bhagavatula; Thanapon Noraset; Doug Downey (IDEA@KDD, 2013)

Overcoming the Memory Bottleneck in Distributed Training of Latent Variable Models of Text. - Yi Yang 042; Alexander Yates; Doug Downey (HLT-NAACL, 2013)

WebSAIL Wikifier: English Entity Linking at TAC 2013. - Thanapon Noraset; Chandra Bhagavatula; Yi Yang 042; Doug Downey (TAC, 2013)

Spam ain't as diverse as it seems: throttling OSN spam with templates underneath. - Hongyu Gao; Yi Yang 042; Kai Bu; Yan Chen 004; Doug Downey; Kathy Lee; Alok N. Choudhary (ACSAC, 2014)

Adding High-Precision Links to Wikipedia. - Thanapon Noraset; Chandra Bhagavatula; Doug Downey (EMNLP, 2014)

Analyzing the content emphasis of web search engines. - Mohammed A. Alam; Doug Downey (SIGIR, 2014)

WebSAIL wikifier at ERD 2014. - Thanapon Noraset; Chandra Bhagavatula; Doug Downey (ERD@SIGIR, 2014)

Learning Representations for Weakly Supervised Natural Language Processing Tasks. - Fei Huang 008; Arun Ahuja; Doug Downey; Yi Yang 042; Yuhong Guo; Alexander Yates (Comput. Linguistics, 2014)

Efficient Methods for Inferring Large Sparse Topic Hierarchies. - Doug Downey; Chandra Bhagavatula; Yi Yang 042 (ACL (1), 2015)

Efficient Methods for Incorporating Knowledge into Topic Models. - Yi Yang 042; Doug Downey; Jordan L. Boyd-Graber (EMNLP, 2015)

TabEL: Entity Linking in Web Tables. - Chandra Sekhar Bhagavatula; Thanapon Noraset; Doug Downey (ISWC (1), 2015)

Learning Hierarchically Decomposable Concepts with Active Over-Labeling. - Yuji Mo; Stephen D. Scott 001; Doug Downey (ICDM, 2016)

Beating the Artificial Chaos: Fighting OSN Spam Using Its Own Templates. - Tiantian Zhu; Hongyu Gao; Yi Yang 042; Kai Bu; Yan Chen 004; Doug Downey; Kathy Lee; Alok N. Choudhary (IEEE/ACM Trans. Netw., 2016)

Definition Modeling: Learning to Define Word Embeddings in Natural Language. - Thanapon Noraset; Chen Liang; Larry Birnbaum; Doug Downey (AAAI, 2017)

PAG2ADMG: A Novel Methodology to Enumerate Causal Graph Structures. - Nishant Subramani; Doug Downey (AAAI, 2017)

VecShare: A Framework for Sharing Word Representation Vectors. - Jared Fernandez; Zhaocheng Yu; Doug Downey (EMNLP, 2017)

Controlling Global Statistics in Recurrent Neural Network Text Generation. - Thanapon Noraset; David Demeter; Doug Downey (AAAI, 2018)

OTyper: A Neural Architecture for Open Named Entity Typing. - Zheng Yuan 004; Doug Downey (AAAI, 2018)

Sampling Informative Training Data for RNN Language Models. - Jared Fernandez; Doug Downey (ACL (3), 2018)

Extracting Commonsense Properties from Embeddings with Limited Human Guidance. - Yiben Yang; Larry Birnbaum; Ji-Ping Wang; Doug Downey (ACL (2), 2018)

Estimating Marginal Probabilities of n-grams for Recurrent Neural Language Models. - Thanapon Noraset; Doug Downey; Lidong Bing (EMNLP, 2018)

Construction of the Literature Graph in Semantic Scholar. - Waleed Ammar; Dirk Groeneveld; Chandra Bhagavatula; Iz Beltagy; Miles Crawford; Doug Downey; Jason Dunkelberger; Ahmed Elgohary; Sergey Feldman; Vu Ha; Rodney Kinney; Sebastian Kohlmeier; et al. (NAACL-HLT (3), 2018)

A new evaluation framework for topic modeling algorithms based on synthetic corpora. - Hanyu Shi 003; Martin Gerlach; Isabel Diersen; Doug Downey; Luis A. Nunes Amaral (AISTATS, 2019)

Using Large Corpus N-gram Statistics to Improve Recurrent Neural Language Models. - Yiben Yang; Ji-Ping Wang; Doug Downey (NAACL-HLT (1), 2019)

A Semantic Cover Approach for Topic Modeling. - Rajagopal Venkatesaramani; Doug Downey; Bradley A. Malin; Yevgeniy Vorobeychik (*SEM@NAACL-HLT, 2019)

CODAH: An Adversarially Authored Question-Answer Dataset for Common Sense. - Michael Chen; Mike D'Arcy; Alisa Liu; Jared Fernandez; Doug Downey (CoRR, 2019)

Multi-sense Definition Modeling using Word Sense Decompositions. - Ruimin Zhu; Thanapon Noraset; Alisa Liu; Wenxin Jiang 003; Doug Downey (CoRR, 2019)

Just Add Functions: A Neural-Symbolic Language Model. - David Demeter; Doug Downey (AAAI, 2020)

SPECTER: Document-level Representation Learning using Citation-informed Transformers. - Arman Cohan; Sergey Feldman; Iz Beltagy; Doug Downey; Daniel S. Weld (ACL, 2020)

Stolen Probability: A Structural Weakness of Neural Language Models. - David Demeter; Gregory Kimmel; Doug Downey (ACL, 2020)

Don't Stop Pretraining: Adapt Language Models to Domains and Tasks. - Suchin Gururangan; Ana Marasovic; Swabha Swayamdipta; Kyle Lo; Iz Beltagy; Doug Downey; Noah A. Smith (ACL, 2020)

G-DAug: Generative Data Augmentation for Commonsense Reasoning. - Yiben Yang; Chaitanya Malaviya; Jared Fernandez; Swabha Swayamdipta; Ronan Le Bras 001; Ji-Ping Wang; Chandra Bhagavatula; Yejin Choi 001; Doug Downey (EMNLP (Findings), 2020)

Abductive Commonsense Reasoning. - Chandra Bhagavatula; Ronan Le Bras 001; Chaitanya Malaviya; Keisuke Sakaguchi; Ari Holtzman; Hannah Rashkin; Doug Downey; Wen-tau Yih; Yejin Choi 001 (ICLR, 2020)

High-Precision Extraction of Emerging Concepts from Scientific Literature. - Daniel King; Doug Downey; Daniel S. Weld (SIGIR, 2020)

Practical Methods for Semi-automated Peer Grading in a Classroom Setting. - Zheng Yuan 004; Doug Downey (UMAP, 2020)

Explanation-Based Tuning of Opaque Machine Learners with Application to Paper Recommendation. - Benjamin Charles Germain Lee; Kyle Lo; Doug Downey; Daniel S. Weld (CoRR, 2020)

SciCo: Hierarchical Cross-Document Coreference for Scientific Concepts. - Arie Cattan; Sophie Johnson; Daniel S. Weld; Ido Dagan; Iz Beltagy; Doug Downey; Tom Hope (AKBC, 2021)

Who's on First?: Probing the Learning and Representation Capabilities of Language Models on Deterministic Closed Domains. - David Demeter; Doug Downey (CoNLL, 2021)

"It doesn't look good for a date": Transforming Critiques into Preferences for Conversational Recommendation Systems. - Victor S. Bursztyn; Jennifer Healey; Nedim Lipka; Eunyee Koh; Doug Downey; Larry Birnbaum (EMNLP (1), 2021)

S2AND: A Benchmark and Evaluation System for Author Name Disambiguation. - Shivashankar Subramanian; Daniel King; Doug Downey; Sergey Feldman (JCDL, 2021)

CODE: Compiler-based Neuron-aware Ensemble training. - Ettore M. G. Trainiti; Thanapon Noraset; David Demeter; Doug Downey; Simone Campanoni (MLSys, 2021)

Simplified Data Wrangling with ir_datasets. - Sean MacAvaney; Andrew Yates; Sergey Feldman; Doug Downey; Arman Cohan; Nazli Goharian (SIGIR, 2021)

Incorporating Visual Layout Structures for Scientific Text Classification. - Zejiang Shen 001; Kyle Lo; Lucy Lu Wang; Bailey Kuehl; Daniel S. Weld; Doug Downey (CoRR, 2021)

CascadER: Cross-Modal Cascading for Knowledge Graph Link Prediction. - Tara Safavi; Doug Downey; Tom Hope (AKBC, 2022)

From Who You Know to What You Read: Augmenting Scientific Recommendations with Implicit Social Networks. - Hyeonsu B. Kang; Rafal Kocielnik; Andrew Head; Jiangjiang Yang; Matt Latzke; Aniket Kittur; Daniel S. Weld; Doug Downey; Jonathan Bragg (CHI, 2022)

Exploring the Role of Local and Global Explanations in Recommender Systems. - Marissa Radensky; Doug Downey; Kyle Lo; Zoran Popovic; Daniel S. Weld (CHI Extended Abstracts, 2022)

Building a Shared Conceptual Model of Complex, Heterogeneous Data Systems: A Demonstration. - Michael R. Anderson; Yuze Lou; Jiayun Zou; Michael J. Cafarella; Sarah E. Chasins; Doug Downey; Tian Gao; Kexin Huang; Dinghao Shen; Jenny M. Vo-Phamhi; Yitong Wang; Yuning Wang; et al. (CIDR, 2022)

Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models. - Victor S. Bursztyn; David Demeter; Doug Downey; Larry Birnbaum (EMNLP (Findings), 2022)

ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of Scientific Concepts. - Sonia K. Murthy; Kyle Lo; Daniel King; Chandra Bhagavatula; Bailey Kuehl; Sophie Johnson; Jonathan Borchardt; Daniel S. Weld; Tom Hope; Doug Downey (EMNLP (Demos), 2022)

S2AMP: a high-coverage dataset of scholarly mentorship inferred from publications. - Shaurya Rohatgi; Doug Downey; Daniel King; Sergey Feldman (JCDL, 2022)

Few-Shot Self-Rationalization with Natural Language Prompts. - Ana Marasovic; Iz Beltagy; Doug Downey; Matthew E. Peters (NAACL-HLT (Findings), 2022)

Multi-LexSum: Real-world Summaries of Civil Rights Lawsuits at Multiple Granularities. - Zejiang Shen 001; Kyle Lo; Lauren Yu; Nathan Dahlberg; Margo Schlanger; Doug Downey (NeurIPS, 2022)

FeedLens: Polymorphic Lenses for Personalizing Exploratory Search over Knowledge Graphs. - Harmanpreet Kaur; Doug Downey; Amanpreet Singh; Evie Yu-Yen Cheng; Daniel S. Weld; Jonathan Bragg (UIST, 2022)

Infrastructure for Rapid Open Knowledge Network Development. - Michael J. Cafarella; Michael R. Anderson; Iz Beltagy; Arie Cattan; Sarah E. Chasins; Ido Dagan; Doug Downey; Oren Etzioni; Sergey Feldman; Tian Gao; Tom Hope; Kexin Huang; et al. (AI Mag., 2022)

Don't Say What You Don't Know: Improving the Consistency of Abstractive Summarization by Constraining Beam Search. - Daniel King; Zejiang Shen 001; Nishant Subramani; Daniel S. Weld; Iz Beltagy; Doug Downey (CoRR, 2022)

I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation. - Chandra Bhagavatula; Jena D. Hwang; Doug Downey; Ronan Le Bras 001; Ximing Lu; Keisuke Sakaguchi; Swabha Swayamdipta; Peter West; Yejin Choi 001 (CoRR, 2022)

ABNIRML: Analyzing the Behavior of Neural IR Models. - Sean MacAvaney; Sergey Feldman; Nazli Goharian; Doug Downey; Arman Cohan (Trans. Assoc. Comput. Linguistics, 2022)

VILA: Improving Structured Content Extraction from Scientific PDFs Using Visual Layout Groups. - Zejiang Shen 001; Kyle Lo; Lucy Lu Wang; Bailey Kuehl; Daniel S. Weld; Doug Downey (Trans. Assoc. Comput. Linguistics, 2022)

I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation. - Chandra Bhagavatula; Jena D. Hwang; Doug Downey; Ronan Le Bras 001; Ximing Lu; Lianhui Qin; Keisuke Sakaguchi; Swabha Swayamdipta; Peter West; Yejin Choi 001 (ACL (1), 2023)

Are Layout-Infused Language Models Robust to Layout Distribution Shifts? A Case Study with Scientific Documents. - Catherine Chen 002; Zejiang Shen 001; Dan Klein 001; Gabriel Stanovsky; Doug Downey; Kyle Lo (ACL (Findings), 2023)

CiteSee: Augmenting Citations in Scientific Papers with Persistent and Personalized Historical Context. - Joseph Chee Chang; Amy X. Zhang; Jonathan Bragg; Andrew Head; Kyle Lo; Doug Downey; Daniel S. Weld (CHI, 2023)

Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections. - Srishti Palani; Aakanksha Naik; Doug Downey; Amy X. Zhang; Jonathan Bragg; Joseph Chee Chang (CHI, 2023)

Penguins Don't Fly: Reasoning about Generics through Instantiations and Exceptions. - Emily Allaway; Jena D. Hwang; Chandra Bhagavatula; Kathleen R. McKeown; Doug Downey; Yejin Choi 001 (EACL, 2023)

Embedding Recycling for Language Models. - Jon Saad-Falcon; Amanpreet Singh; Luca Soldaini; Mike D'Arcy; Arman Cohan; Doug Downey (EACL (Findings), 2023)

CHAMP: Efficient Annotation and Consolidation of Cluster Hierarchies. - Arie Cattan; Tom Hope; Doug Downey; Roy Bar-Haim; Lilach Eden; Yoav Kantor; Ido Dagan (EMNLP (Demos), 2023)

PaperMage: A Unified Toolkit for Processing, Representing, and Manipulating Visually-Rich Scientific Documents. - Kyle Lo; Zejiang Shen 001; Benjamin Newman; Joseph Chee Chang; Russell Authur; Erin Bransom; Stefan Candra; Yoganand Chandrasekhar; Regan Huff; Bailey Kuehl; Amanpreet Singh; Chris Wilhelm; et al. (EMNLP (Demos), 2023)

S2abEL: A Dataset for Entity Linking from Scientific Tables. - Yuze Lou; Bailey Kuehl; Erin Bransom; Sergey Feldman; Aakanksha Naik; Doug Downey (EMNLP, 2023)

SciRepEval: A Multi-Format Benchmark for Scientific Document Representations. - Amanpreet Singh; Mike D'Arcy; Arman Cohan; Doug Downey; Sergey Feldman (EMNLP, 2023)

The Semantic Scholar Open Data Platform. - Rodney Kinney; Chloe Anastasiades; Russell Authur; Iz Beltagy; Jonathan Bragg; Alexandra Buraczynski; Isabel Cachola; Stefan Candra; Yoganand Chandrasekhar; Arman Cohan; Miles Crawford; Doug Downey; et al. (CoRR, 2023)

The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces. - Kyle Lo; Joseph Chee Chang; Andrew Head; Jonathan Bragg; Amy X. Zhang; Cassidy Trier; Chloe Anastasiades; Tal August; Russell Authur; Danielle Bragg; Erin Bransom; Isabel Cachola; et al. (CoRR, 2023)

Beyond Summarization: Designing AI Support for Real-World Expository Writing Tasks. - Zejiang Shen 001; Tal August; Pao Siangliulue; Kyle Lo; Jonathan Bragg; Jeff Hammerbacher; Doug Downey; Joseph Chee Chang; David A. Sontag (CoRR, 2023)

Learning to Generate Novel Scientific Directions with Contextualized Literature-based Discovery. - Qingyun Wang 005; Doug Downey; Heng Ji 001; Tom Hope (CoRR, 2023)

A Computational Inflection for Scientific Discovery. - Tom Hope; Doug Downey; Daniel S. Weld; Oren Etzioni; Eric Horvitz (Commun. ACM, 2023)

LIMEADE: From AI Explanations to Advice Taking. - Benjamin Charles Germain Lee; Doug Downey; Kyle Lo; Daniel S. Weld (ACM Trans. Interact. Intell. Syst., 2023)

SciMON: Scientific Inspiration Machines Optimized for Novelty. - Qingyun Wang 005; Doug Downey; Heng Ji 001; Tom Hope (ACL (1), 2024)

ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews. - Mike D'Arcy; Alexis Ross; Erin Bransom; Bailey Kuehl; Jonathan Bragg; Tom Hope; Doug Downey (ACL (1), 2024)

TOPICAL: TOPIC Pages AutomagicaLly. - John M. Giorgi; Amanpreet Singh; Doug Downey; Sergey Feldman; Lucy Lu Wang (NAACL (Demonstrations), 2024)

CARE: Extracting Experimental Findings From Clinical Literature. - Aakanksha Naik; Bailey Kuehl; Erin Bransom; Doug Downey; Tom Hope (NAACL-HLT (Findings), 2024)

MARG: Multi-Agent Review Generation for Scientific Papers. - Mike D'Arcy; Tom Hope; Larry Birnbaum; Doug Downey (CoRR, 2024)

SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature. - David Wadden; Kejian Shi; Jacob Morrison; Aakanksha Naik; Shruti Singh 001; Nitzan Barzilay; Kyle Lo; Tom Hope; Luca Soldaini; Shannon Zejiang Shen; Doug Downey; Hannaneh Hajishirzi; et al. (CoRR, 2024)

OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs. - Akari Asai; Jacqueline He; Rulin Shao; Weijia Shi; Amanpreet Singh; Joseph Chee Chang; Kyle Lo; Luca Soldaini; Sergey Feldman; Mike D'Arcy; David Wadden; Matt Latzke; et al. (CoRR, 2024)

The Semantic Reader Project. - Kyle Lo; Joseph Chee Chang; Andrew Head; Jonathan Bragg; Amy X. Zhang; Cassidy Trier; Chloe Anastasiades; Tal August; Russell Authur; Danielle Bragg; Erin Bransom; Isabel Cachola; et al. (Commun. ACM, 2024)

Ai2 Scholar QA: Organized Literature Synthesis with Attribution. - Amanpreet Singh; Joseph Chee Chang; Chloe Anastasiades; Dany Haddad; Aakanksha Naik; Amber Tanaka; Angele Zamarron; Cecile Nguyen; Jena D. Hwang; Jason Dunkleberger; Matt Latzke; Smita Rao; et al. (CoRR, 2025)

SciArena: An Open Evaluation Platform for Foundation Models in Scientific Literature Tasks. - Yilun Zhao 001; Kaiyan Zhang; Tiansheng Hu; Sihong Wu; Ronan Le Bras 001; Taira Anderson; Jonathan Bragg; Joseph Chee Chang; Jesse Dodge; Matt Latzke; Yixin Liu 003; Charles McGrady; et al. (CoRR, 2025)

Setting The Table with Intent: Intent-aware Schema Generation and Editing for Literature Review Tables. - Vishakh Padmakumar; Joseph Chee Chang; Kyle Lo; Doug Downey; Aakanksha Naik (CoRR, 2025)