A Profile in Statistics of Journal Articles: Fifty Years of American Documentation and the Journal of the American Society for Information Science
By W. Koehler. 2000
142 citations recorded by the source corpus.
Subfields: Evaluation & Benchmarks, Social Sciences & Humanities
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Evaluation & Benchmarks
- Shimon Whiteson
- Kurt Shuster
- Wen-tau Yih
- Patrick Lewis
- Danqi Chen
- Sewon Min
- Samuel Humeau
- Chris Alberti
In Social Sciences & Humanities
- Marie-Anne Lachaux
- Jason Aaron Edward Weston
- Jakob N. Foerster
- Chaochao Chen
- Shimon Whiteson
- Jelena Luketina
- Edward Grefenstette
- Feng Zhu
Citations in the corpus
- Dense Passage Retrieval for Open-Domain Question Answering (2020, background): “In contrast to unsupervised dimensionality reduction methods (e.g., LSA), leveraging labeled data to train dense encoders for embedding both documents and queries has become popular recently (Yih et al., 2011; Huang et al., 2013; Gillick et al., 2019; Humeau et al., 2019).”
- Fusion of Detected Objects in Text for Visual Question Answering (2019, background): “It has long been understood that the meaning of a word is systematically and predictably linked to the context in which it occurs (e.g., Firth 1957; Harris 1954; Deerwester et al. 1990; Mikolov et al. 2013).”
- A Survey of Reinforcement Learning Informed by Natural Language (2019, methodology): “Current NLP systems commonly employ deep learning models and represent (sequences of) words using dense vector representations that are either pre-trained from large textual corpora or that are learned from scratch for the task at hand [Deerwester et al., 1990; Mikolov et al., 2013; Peters et al., 2”
- Multi-Task Retrieval for Knowledge-Intensive Tasks (2021, background): “Whether a passage is relevant to a given query is determined by the distance of their vectors (Deerwester et al., 1990).”
- Cross-Domain Recommendation: Challenges, Progress, and Prospects (2021, methodology): “This class involves first training different CF-based models (such as singular value decomposition [ Deerwester et al. , 1990 ] , maximum-margin matrix factorisation [ Srebro et al. , 2005 ] , probabilistic matrix factorisation [ Mnih and Salakhutdinov, 2007 ] , bayesian personalised ranking […”
- Real-time Inference in Multi-sentence Tasks with Deep Pretrained Transformers (2019, methodology): “Such methods include vector space models (Salton et al., 1975), LSI (Deerwester et al., 1990), supervised embeddings (Bai et al., 2009) and classical siamese networks (Bromley et al., 1994).”