Publications

This page contains a list of manuscripts that I have authored. For bibliographic information, please refer to my Semantic Scholar or Google Scholar profiles.

* indicates equal contribution; † indicates core contributors.

2025

Alexander Wettig, Kyle Lo, Sewon Min, Hannaneh Hajishirzi, Danqi Chen, and Luca Soldaini. “Organize the Web: Constructing Domains Enhances Pre-Training Data Curation”. ICML 2025.
Ian Magnusson*, Nguyen Tai*, Ben Bogin*, David Heineman, Jena D. Hwang, Luca Soldaini, Akshita Bhagia, Jiacheng Liu, Dirk Groeneveld, Oyvind Tafjord, Noah A. Smith, Pang Wei Koh, and Jesse Dodge. “DataDecide: How to Predict Best Pretraining Data with Small Experiments”. ICML 2025.
Jake Poznanski^†, Jon Borchardt, Jason Dunkelberger, Regan Huff, Daniel Lin, Aman Rangapur, Christopher Wilhelm, Kyle Lo^†, and Luca Soldaini^†. “olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models”. ArXiv 2502.18443. preprint
Sami Baral, Li Lucy, Ryan Knight, Alice Ng, Luca Soldaini, Neil T. Heffernan, and Kyle Lo. “DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students’ Hand-Drawn Math Images”. NAACL 2025. outstanding paper award
Orion Weller, Benjamin Chang, Sean MacAvaney, Kyle Lo, Arman Cohan, Benjamin Van Durme, Dawn Lawrie, and Luca Soldaini. “FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions”. NAACL 2025.
Jiacheng Liu, Taylor Blanton, Yanai Elazar, Sewon Min, YenSung Chen, Arnavi Chheda-Kothary, Huy Tran, Byron Bischoff, Eric Marsh, Michael Schmitz, Cassidy Trier, Aaron Sarnat, Jenna James, Jon Borchardt, Bailey Kuehl, Evie Cheng, Karen Farley, Sruthi Sreeram, Taira Anderson, David Albright, Carissa Schoenick, Luca Soldaini, Dirk Groeneveld, Rock Yuren Pang, Pang Wei Koh, Noah A. Smith, Sophie Lebrecht, Yejin Choi, Hannaneh Hajishirzi, Ali Farhadi, and Jesse Dodge. “OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens”. preprint
Niklas Muennighoff, Luca Soldaini, Dirk Groeneveld, Kyle Lo, Jacob Morrison, Sewon Min, Weijia Shi, Pete Walsh, Oyvind Tafjord, Nathan Lambert, Yuling Gu, Shane Arora, Akshita Bhagia, Dustin Schwenk, David Wadden, Alexander Wettig, Binyuan Hui, Tim Dettmers, Douwe Kiela, Ali Farhadi, Noah A. Smith, Pang Wei Koh, Amanpreet Singh, and Hannaneh Hajishirzi. “OLMoE: Open Mixture-of-Experts Language Models”. ICLR 2025. oral
Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Luca Soldaini, Alexandros G. Dimakis, Gabriel Ilharco, Pang Wei Koh, Shuran Song, Thomas Kollar, Yair Carmon*, Achal Dave*, Reinhard Heckel*, Niklas Muennighoff*, and Ludwig Schmidt*. “Language models scale reliably with over-training and on downstream tasks”. ICLR 2025.
Matt Deitke, Christopher Clark, Sangho Lee, Rohun Tripathi, Yue Yang, Jae Sung Park, Mohammadreza Salehi, Niklas Muennighoff, Kyle Lo, Luca Soldaini, Jiasen Lu, Taira Anderson, Erin Bransom, Kiana Ehsani, Huong Ngo, YenSung Chen, Ajay Patel, Mark Yatskar, Chris Callison-Burch, Andrew Head, Rose Hendrix, Favyen Bastani, Eli VanderBilt, Nathan Lambert, Yvonne Chou, Arnavi Chheda, Jenna Sparks, Sam Skjonsberg, Michael Schmitz, Aaron Sarnat, Byron Bischoff, Pete Walsh, Chris Newell, Piper Wolters, Tanmay Gupta, Kuo-Hao Zeng, Jon Borchardt, Dirk Groeneveld, Jen Dumas, Crystal Nam, Sophie Lebrecht, Caitlin Wittlif, Carissa Schoenick, Oscar Michel, Ranjay Krishna, Luca Weihs, Noah A. Smith, Hannaneh Hajishirzi, Ross Girshick, Ali Farhadi, and Aniruddha Kembhavi. “Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models”. CVPR 2025.
Orion Weller, Benjamin Chang, Eugene Yang, Mahsa Yarmohammadi, Sam Barham, Sean MacAvaney, Arman Cohan, Luca Soldaini, Benjamin Van Durme, and Dawn Lawrie. “mFollowIR: a Multilingual Benchmark for Instruction Following in Information Retrieval”. ECIR 2025.
Team OLMo: Pete Walsh^†, Luca Soldaini^†, Dirk Groeneveld^†, Kyle Lo^†, Shane Arora^†, Akshita Bhagia^†, Yuling Gu^†, Shengyi Huang^†, Matt Jordan^†, Nathan Lambert^†, Dustin Schwenk^†, Oyvind Tafjord^†, Taira Anderson, David Atkinson, Faeze Brahman, Christopher Clark, Pradeep Dasigi, Nouha Dziri, Michal Guerquin, Hamish Ivison, Pang Wei Koh, Jiacheng Liu, Saumya Malik, William Merrill, Lester James V. Miranda, Jacob Morrison, Tyler Murray, Crystal Nam, Valentina Pyatkin, Aman Rangapur, Michael Schmitz, Sam Skjonsberg, David Wadden, Christopher Wilhelm, Michael Wilson, Luke Zettlemoyer, Ali Farhadi, Noah A. Smith^†, and Hannaneh Hajishirzi^†. “2 OLMo 2 Furious”. ArXiv 2501.00656. preprint
Hyunji Lee, Luca Soldaini, Arman Cohan, Minjoon Seo, and Kyle Lo. RouterRetriever: Exploring the Benefits of Routing over Multiple Expert Embedding Models. AAAI 2025.

2024

Akshita Bhagia*, Jiacheng Liu*, Alexander Wettig, David Heineman, Oyvind Tafjord, Ananya Harsh Jha, Luca Soldaini, Noah A. Smith, Dirk Groeneveld, Pang Wei Koh, Jesse Dodge, and Hannaneh Hajishirzi. “Establishing Task Scaling Laws via Compute-Efficient Model Ladders”. ArXiv 2412.04403. preprint
Shayne Longpre*, Stella Biderman*, Alon Albalak, Hailey Schoelkopf, Daniel McDuff, Sayash Kapoor, Kevin Klyman, Kyle Lo, Gabriel Ilharco, Nay San, Maribeth Rauh, Aviya Skowron, Bertie Vidgen, Laura Weidinger, Arvind Narayanan, Victor Sanh, David Adelani, Percy Liang, Rishi Bommasani, Peter Henderson, Sasha Luccioni, Yacine Jernite*, and Luca Soldaini*. “The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources”. TMLR 12/2024.
Nathan Lambert, Jacob Morrison, Valentina Pyatkin, Shengyi Huang, Hamish Ivison, Faeze Brahman,Lester James V. Miranda, Alisa Liu, Nouha Dziri, Xinxi Lyu, Yuling Gu, Saumya Malik, Victoria Graf, Jena D. Hwang, Jiangjiang Yang, Ronan Le Bras, Oyvind Tafjord, Chris Wilhelm, Luca Soldaini, Noah A. Smith, Yizhong Wang, Pradeep Dasigi, and Hannaneh Hajishirzi. “Tülu 3: Pushing Frontiers in Open Language Model Post-Training”. ArXiv 2411.15124. preprint
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, Minyang Tian, Pan Ji, Shengyan Liu, Hao Tong, Bohao Wu, Yanyu Xiong, Luke Zettlemoyer, Graham Neubig, Dan Weld, Doug Downey, Wen-tau Yih, Pang Wei Koh, and Hannaneh Hajishirzi. “OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs”. ArXiv 2411.14199. preprint
Li Lucy, Tal August, Rose E. Wang, Luca Soldaini, Courtney Allison, and Kyle Lo. “MathFish 🐟: Evaluating Language Model Math Reasoning via Grounding in Educational Curricula”. Findings of EMNLP 2024.
Jeffrey Li^†, Alex Fang^†, Georgios Smyrnis^†, Maor Ivgi^†, Matt Jordan, Samir Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Chandu, Thao Nguyen, Igor Vasiljevic, Sham Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave^†, Ludwig Schmidt^†, and Vaishaal Shankar^†. “DataComp-LM: In search of the next generation of training sets for language models”. Datasets and Benchmarks track, NeurIPS 2024.
Ian Magnusson, Akshita Bhagia, Valentin Hofmann, Luca Soldaini, Ananya Harsh Jha, Oyvind Tafjord, Dustin Schwenk, Evan Pete Walsh, Yanai Elazar, Kyle Lo, Dirk Groeneveld, Iz Beltagy, Hannaneh Hajishirzi, Noah A. Smith, Kyle Richardson, and Jesse Dodge. “Paloma: A Benchmark for Evaluating Language Model Fit”. Datasets and Benchmarks track, NeurIPS 2024.
Raymond Fok, Luca Soldaini, Cassidy Trier, Erin Bransom, Kelsey MacMillan, Evie Cheng, Hita Kambhamettu, Jonathan Bragg, Kyle Lo, Marti A. Hearst, Andrew Head, and Daniel S. Weld. “Accelerating Scientific Paper Skimming with Augmented Intelligence Through Customizable Faceted Highlights”. ACM Transactions on Interactive Intelligent Systems 2024.
Nathan Lambert, Hailey Schoelkopf, Aaron Gokaslan, Luca Soldaini, Valentina Pyatkin, and Louis Castricato. “Self-Directed Synthetic Dialogues and Revisions Technical Report”. ArXiv 2407.18421. technical report
David Wadden*, Kejian Shi*, Jacob Morrison, Aakanksha Naik, Shruti Singh, Nitzan Barzilay, Kyle Lo, Tom Hope, Luca Soldaini, Shannon Zejiang Shen, Doug Downey, Hannaneh Hajishirzi, and Arman Cohan. “SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature”. ArXiv 2406.07835.
James Mayfield, Eugene Yang, Dawn Lawrie, Sean MacAvaney, Paul McNamee, Douglas W. Oard, Luca Soldaini, Ian Soboroff, Orion Weller, Efsun Kayi, Kate Sanders, Marc Mason, and Noah Hibbler. “On the Evaluation of Machine-Generated Reports”. SIGIR 2024. best paper nomination
Fangyuan Xu, Kyle Lo, Luca Soldaini, Bailey Kuehl, Eunsol Choi, and David Wadden. “KIWI: A Dataset of Knowledge-Intensive Writing Instructions for Answering Research Questions”. Findings of ACL 2024.
Luca Soldaini^†, Rodney Kinney^†, Akshita Bhagia^†, Dustin Schwenk^†, David Atkinson, Russell Authur, Ben Bogin, Khyathi 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, and Kyle Lo^†. “Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research”. ACL 2024. best paper award
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, and Hannaneh Hajishirzi. “OLMo: Accelerating the Science of Language Models”. ACL 2024. best paper award
Li Lucy, Suchin Gururangan, Luca Soldaini, Emma Strubell, David Bamman, Lauren Klein, and Jesse Dodge. “AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters”. ACL 2024.
James Mayfield, Eugene Yang, Dawn Lawrie, Sean MacAvaney, Paul McNamee, Douglas W. Oard, Luca Soldaini, Ian Soboroff, Orion Weller, Efsun Kayi, Kate Sanders, Marc Mason, and Noah Hibbler. “On the Evaluation of Machine-Generated Reports”. Perspective paper, SIGIR 2024.
Orion Weller, Kyle Lo, David Wadden, Dawn Lawrie, Benjamin Van Durme, Arman Cohan, and Luca Soldaini. “When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasets”. Findings of EACL 2024.
Yanai Elazar, Akshita Bhagia, Ian Magnusson, Abhilasha Ravichander, Dustin Schwenk, Alane Suhr, Pete Walsh, Dirk Groeneveld, Luca Soldaini, Sameer Singh, Hanna Hajishirzi, Noah A. Smith, and Jesse Dodge. “What’s In My Big Data?” ICLR 2024. spotlight

2023

Hyunji Lee, Luca Soldaini, Arman Cohan, Minjoon Seo, and Kyle Lo. “Back to Basics: A Simple Recipe for Improving Out-of-Domain Retrieval in Dense Encoders”. ArXiv 2311.09765.
Kyle Lo^†, Zejiang Shen^†, Benjamin Newman^†, Joseph Chee Chang^†, Russell Authur, Erin Bransom, Stefan Candra, Yoganand Chandrasekhar, Regan Huff, Bailey Kuehl, Amanpreet Singh, Chris Wilhelm, Angele Zamarron, Marti A. Hearst, Daniel S. Weld, Doug Downey, and Luca Soldaini^†. “PaperMage: A Unified Toolkit for Processing, Representing, and Manipulating Visually-Rich Scientific Documents”. System Demonstration, EMNLP 2023. best paper award
Benjamin Newman, Luca Soldaini, Raymond Fok, Arman Cohan, and Kyle Lo “A Question Answering Framework for Decontextualizing User-facing Snippets from Scientific Documents”. EMNLP 2023.
John Giorgi, Luca Soldaini, Bo Wang, Gary Bader, Kyle Lo, Lucy Lu Wang, and Arman Cohan. “Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval”. Findings of EMNLP 2023.
Dawn Lawrie, Sean MacAvaney, James Mayfield, Paul McNamee, Douglas W. Oard, Luca Soldaini, and Eugene Yang. Overview of the TREC 2023 NeuCLIR Track. TREC 2023.
Pratyusha Ria Kalluri*, William Agnew*, Myra Cheng*, Kentrell Owens*, Luca Soldaini*, and Abeba Birhane*. “The Surveillance AI Pipeline”. ArXiv 2309.15084.
Raymond Fok, Hita Kambhamettu, Luca Soldaini, Jonathan Bragg, Kyle Lo, Andrew Head, Marti A. Hearst, and Daniel S. Weld. “SCIM: Intelligent Skimming Support for Scientific Papers”. IUI 2023.
Organizers of Queer in AI, Nathan Dennler, Anaelia Ovalle, Ashwin Singh, Luca Soldaini, Arjun Subramonian, Huy Tu, William Agnew, Avijit Ghosh, Kyra Yee, Irene Font Peradejordi, Zeerak Talat, Mayra Russo, and Jess de Jesus de Pinho Pinhal. “Bound to the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms”. AIES 2023.
Organizers of Queer in AI, Anaelia Ovalle*, Arjun Subramonian*, Ashwin Singh*, Claas Voelcker*, Danica J. Sutherland*, Davide Locatelli*, Eva Breznik*, Filip Klubička*, Hang Yuan*, Hetvi J*, Huan Zhang*, Jaidev Shriram*, Kruno Lehman*, Luca Soldaini*, Maarten Sap*, Marc Peter Deisenroth*, Maria Leonor Pacheco*, Maria Ryskina*, Martin Mundt*, Melvin Selim Atay*, Milind Agarwal*, Nyx McLean*, Pan Xu*, A Pranav*, Raj Korpan*, Ruchira Ray*, Sarah Mathew*, Sarthak Arora*, St John*, Tanvi Anand*, Vishakha Agrawal*, William Agnew*, Yanan Long*, Zijie J. Wang*, Zeerak Talat*, Avijit Ghosh*, Nathaniel Dennler*, Michael Noseworthy*, Sharvani Jha*, Emi Baylor*, Aditya Joshi*, Natalia Y. Bilenko*, Andrew McNamara*, Raphael Gontijo-Lopes*, Alex Markham*, Evyn Dǒng*, Jackie Kay*, Manu Saraswat*, Nikhil Vytla*, and Luke Stark*. “Queer In AI: A Case Study in Community-Led Participatory AI”. FAccT 2023. best paper award
Sean MacAvaney* and Luca Soldaini*. “One-Shot Labeling for Automatic Relevance Estimation” Short paper, SIGIR 2023.
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, Stefan Candra, Yoganand Chandrasekhar, Yen-Sung Chen, Evie Yu-Yen Cheng, Yvonne Chou, Doug Downey, Rob Evans, Raymond Fok, Fangzhou Hu, Regan Huff, Dongyeop Kang, Tae Soo Kim, Rodney Kinney, Aniket Kittur, Hyeonsu Kang, Egor Klevak, Bailey Kuehl, Michael Langan, Matt Latzke, Jaron Lochner, Kelsey MacMillan, Eric Marsh, Tyler Murray, Aakanksha Naik, Ngoc-Uyen Nguyen, Srishti Palani, Soya Park, Caroline Paulic, Napol Rachatasumrit, Smita Rao, Paul Sayre, Zejiang Shen, Pao Siangliulue, Luca Soldaini, Huy Tran, Madeleine van Zuylen, Lucy Lu Wang, Christopher Wilhelm, Caroline Wu, Jiangjiang Yang, Angele Zamarron, Marti A. Hearst, and Daniel S. Weld. The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces. ArXiv 2303.14334.
Rodney Michael Kinney, Chloe Anastasiades, Russell Authur, Iz Beltagy, Jonathan Bragg, Alexandra Buraczynski, Isabel Cachola, Stefan Candra, Yoganand Chandrasekhar, Arman Cohan, Miles Crawford, Doug Downey, Jason Dunkelberger, Oren Etzioni, R. Evans, Sergey Feldman, Joseph Gorney, D. Graham, F.Q. Hu, Regan Huff, Daniel King, Sebastian Kohlmeier, Bailey Kuehl, Michael Langan, Daniel Lin, Haokun Liu, Kyle Lo, Jaron Lochner, Kelsey MacMillan, Tyler Murray, Christopher Newell, Smita Rao, Shaurya Rohatgi, P. Sayre, Zejiang Shen, Amanpreet Singh, Luca Soldaini, Shivashankar Subramanian, A. Tanaka, Alex D Wade, Linda M. Wagner, Lucy Lu Wang, Christopher Wilhelm, Caroline Wu, Jiangjiang Yang, A. Zamarron, Madeleine van Zuylen, and Daniel S. Weld. “The Semantic Scholar Open Data Platform”. ArXiv 2302.11266.
Jon Saad-Falcon, Amanpreet Singh, Luca Soldaini, Mike D’Arcy, Arman Cohan, and Doug Downey. “Embedding Recycling for Language Models”. Findings of EACL 2023.

2022

Matteo Gabburo, Rik Koncel-Kedziorski, Siddhant Garg, Luca Soldaini, and Alessandro Moschitti. “Knowledge Transfer from Answer Ranking to Answer Generation”. EMNLP 2022.
Luca Di Liello, Siddhant Garg, Luca Soldaini, and Alessandro Moschitti. “Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection”. Short paper, EMNLP 2022.
Yoshitomo Matsubara, Luca Soldaini, Eric Lind, and Alessandro Moschitti. “Ensemble Transformer for Efficient and Accurate Ranking Tasks: an Application to Question Answering Systems”. Findings of EMNLP 2022.
Dawn Lawrie, Sean MacAvaney, James Mayfield, Paul McNamee, Douglas W. Oard, Luca Soldaini, and Eugene Yang. Overview of the TREC 2022 NeuCLIR Track. TREC 2022.
Benjamin Muller, Luca Soldaini, Rik Koncel-Kedziorski, Eric Lind, and Alessandro Moschitti. “Cross-Lingual GenQA: A Language-Agnostic Generative Question Answering Approach for Open-Domain Question Answering”. AACL 2022.
Luca Di Liello, Siddhant Garg, Luca Soldaini, and Alessandro Moschitti. “Paragraph-based Transformer Pre-training for Multi-Sentence Inference”. Short paper, NAACL-HLT 2022.

2021

Chao-Chun Hsu, Eric Lind, Luca Soldaini, and Alessandro Moschitti. “Answer Generation for Retrieval-based Question Answering Systems”. Findings of ACL 2021.
Rujun Han, Luca Soldaini, and Alessandro Moschitti. “Modeling Context in Answer Sentence Selection Systems on a Latency Budget” EACL 2021.

2020

Mingda Li, Xinyue Liu, Weitong Ruan, Luca Soldaini, Wael Hamza, and Chengwei Su. “Multi-task Learning of Spoken Language Understanding by Integrating N-Best Hypotheses with Hierarchical Attention”. COLING 2020.
Luca Soldaini and Alessandro Moschitti. “The Cascade Transformer: Efficient Answer Sentence Selection”. ACL 2020.
Subendhu Rongali, Luca Soldaini, Emilio Monti, and Wael Hamza. “Don’t Parse, Generate! A Sequence to Sequence Architecture for Task-Oriented Semantic Parsing”. Short paper, WWW 2020.
Sean MacAvaney, Luca Soldaini, and Nazli Goharian. “Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-shot Learning”. Short paper, ECIR 2020.

2018

Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, and Ophir Frieder. “Overcoming Low-Utility Facets for Complex Answer Retrieval”. Information Retrieval Journal, 2018.
Ziling Fan, Luca Soldaini, Arman Cohan, and Nazli Goharian. “Relation Extraction for Protein-Protein Interactions Affected by Mutation”. Short paper, ACM-BCB 2018.
Arman Cohan*, Bart Desmet*, Andrew Yates*, Luca Soldaini, Sean MacAvaney, and Nazli Goharian. “SMHD: a Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions”. COLING 2018.
Luca Soldaini, Timothy Walsh, Arman Cohan, Julien Han, and Nazli Goharian. “Helping or Hurting? Predicting Changes in Users’ Risk of Self-Harm Through Online Community Interactions”. CLPsych Workshop, NAACL-HLT 2018.
Luca Soldaini. “The Knowledge and Language Gap in Medical Information Seeking”. PhD Thesis, Georgetown University. 2018.
Sean MacAvaney, Bart Desmet, Arman Cohan, Luca Soldaini, Andrew Yates, Ayah Zirikly, and Nazli Goharian. “RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses”. CLPsych Workshop, NAACL-HLT 2018.
Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, and Ophir Frieder. “Characterizing Question Facets for Complex Answer Retrieval”. SIGIR 2018.
Sean MacAvaney, Luca Soldaini, Arman Cohan, and Nazli Goharian. “Tree-LSTMs for Scientific Relation Classification”. SemEval Workshop, NAACL-HLT 2018.

2017

Luca Soldaini, Andrew Yates, and Nazli Goharian. “Denoising Clinical Notes for Medical Literature Retrieval with Convolutional Neural Model”. Short paper, CIKM 2017.
Luca Soldaini, Andrew Yates, and Nazli Goharian. “Learning to Reformulate Long Queries for Clinical Decision Support”. JASIST 2017.
Luca Soldaini and Elad Yom-Tov. “Inferring Individual Attributes from Search Engine Queries and Auxiliary Information”. WWW 2017.
Luca Soldaini and Nazli Goharian. “Learning to Rank for Consumer Health Search: a Semantic Approach”. Short paper, ECIR 2017.

2016

Luca Soldaini and Nazli Goharian. “QuickUMLS: a Fast, Unsupervised Approach for Medical Concept Extraction”. MedIR workshop, SIGIR 2016.
Arman Cohan, Luca Soldaini, and Nazli Goharian. “Identifying Significance of Discrepancies in Radiology Reports”. DMMH Workshop, SDM 2016.
Luca Soldaini, Andrew Yates, Elad Yom-Tov, Ophir Frieder, and Nazli Goharian. “Enhancing Web Search in the Medical Domain via Query Clarification”. Information Retrieval Journal, 2016.

2015

Arman Cohan, Luca Soldaini, and Nazli Goharian. “Matching Citation Text and Cited Spans in Biomedical Literature: a Search–Oriented Approach”. Short paper, NAACL-HLT 2015.
Luca Soldaini, Arman Cohan, Andrew Yates, Nazli Goharian, and Ophir Frieder. “Retrieving Medical Literature for Clinical Decision Support”. ECIR 2015.

2014

Arman Cohan, Luca Soldaini, Andrew Yates, Nazli Goharian, and Ophir Frieder. “On Clinical Decision Support”. Short paper, ACM-BCB 2014.