Publications
Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field.
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1 - 15 of 359 publications
Data Mining and Modeling
First Passage Percolation with Queried Hints
Kritkorn Karntikoon
Aaron Schild
Yiheng Shen
Ali Sinop
AISTATS (2024)
Efficient Location Sampling Algorithms for Road Networks
Vivek Kumar
Ameya Velingker
Santhoshini Velusamy
WebConf (2024)
LinguaMeta: Unified Metadata for Thousands of Languages
Uche Okonkwo
Emily Drummond
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Shorts vs. Regular Videos on YouTube: A Comparative Analysis of User Engagement and Content Creation Trends
Caroline Violot
Tugrulcan Elmais
Mathias Humbert
ACM Web Science Conference 2024 (WEBSCI24) (2024)
Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems
Shuo Yang
Aniruddh Nath
Yang Liu
Li Wei
Shawn Andrews
Maciej Kula
Jarrod Kahn
Zhe Zhao
Lichan Hong
2024
Business Intelligence Career Master Plan
Danny Moncada
Eduardo Chavez
Packt (2023) (to appear)
Text Injection for Capitalization and Turn-taking Prediction In ASR Models
Weiran Wang
Zhong Meng
Interspeech 2023 (2023)
Transformers as Graph-to-Graph Models
James Henderson
Alireza Mohammadshahi
Andrei C. Coman
The Big Picture Workshop, ACL,
(2023)
HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Prompting
Jiaying Lu
Bo Xiong
Wenjing Ma
Steffen Staab
Carl Yang
Proc. of The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (2023)
Personalisation in digital ecomuseums: the case of Pros-Eleusis
Ektor Vrettakis
Akrivi Katifori
Myrto Koukouli
Maria Boile
Apostolos Glenis
Dimitra Petousi
Maria Vayanou
Yannis Ioannidis
MDPI , Applied Sciences (2023) (to appear)
Cold-Start Data Selection for Better Few-shot Language Model Fine-tuning: A Prompt-based Uncertainty Propagation Approach
Yue Yu
Rongzhi Zhang
Ran Xu
Jieyu Zhang
Chao Zhang
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL) (2023)