Best Short Paper Awards

We have given a Best Short Paper Award starting from the SIGIR Conference 2017 in Tokyo, Japan. Prior that, we used to have Best Poster Awards given until 1999. Since 2019, the SIGIR Best Short Paper Award is an official ACM Award.

Year Authors Citation
2024 Alireza Salemi
Hamed Zamani
Evaluating Retrieval Quality in Retrieval-Augmented Generation
2023 Weize Kong
Jeffrey M. Dudek
Cheng Li
Mingyang Zhang
Michael Bendersky
SparseEmbed: Learning Sparse Lexical Representations with Contextual Embeddings for Retrieval
2022 Hansi Zeng
Hamed Zamani
Vishwa Vinay
Curriculum Learning for Dense Retrieval Distillation
2021 Xuanang Chen
Ben He
Kai Hui
Yiran Wang
Le Sun
Yingfei Sun
Contextualized Offline Relevance Weighting for Efficient and Effective Neural Retrieval
2020 Shi Yu
Jiahua Liu
Jingqin Yang
Chenyan Xiong
Paul Bennett
Jianfeng Gao
Zhiyuan Liu
Few-Shot Generative Conversation Query Rewriting
2019 Theodore Vasiloudis
Hyunsu Cho
Henrik Boström
Block-distributed Gradient Boosted Trees
2019 Wei Yang
Kuang Lu
Peilin Yang
Jimmy Lin
(Honourable Mention) Critically Examining the “Neural Hype”: Weak Baselines and the Additivity of Effectiveness Gains from Neural Ranking Models
2018 Daniel Cohen
Bhaskar Mitra
Katja Hofmann
W. Bruce Croft
Cross Domain Regularization for Neural Ranking Models using Adversarial Learning
2018 Mengyang Liu
Yiqun Liu
Jiaxin Mao
Cheng Luo
Shaoping Ma
(Honourable Mention) Towards Designing Better Session Search Evaluation Metrics
2017 (first year of award) Michael R. Evans
Dragomir Yankov
Pavel Berkhin
Pavel Yudin
Florin Teodorescu
Wei Wu
LiveMaps – Converting Map Images into Interactive Maps
2017 (first year of award) Faegheh Hasibi
Fedor Nikolaev
Chenyan Xiong
Krisztian Balog
Svein Erik Bratsberg
Alexander Kotov
Jamie Callan
(Honorable Mention) DBpedia-Entity v2: A Test Collection for Entity Search
1998 Ming-Jer Lee
Lee-Feng Chien
Automatic acquisition of phrasal knowledge for English-Chinese bilingual information retrieval
1997 K. Ng
V. Zue
An investigation of subword unit representations for spoken document retrieval