30 citations · 32 across the 7 of their papers we have counts for
6 papers · 1 filter
What If: Generating Code to Answer Simulation Questions
Gal Peretz, Kira Radinsky
Many texts, especially in chemistry and biology, describe complex processes. We focus on texts that describe a chemical reaction process and questions that ask about the process's…
Temporal Attention for Language Models
Guy D. Rosin, Kira Radinsky
Pretrained language models based on the transformer architecture have shown great success in NLP. Textual training data often comes from the web and is thus tagged with time-specif…
Generating Timelines by Modeling Semantic Change
Guy D. Rosin, Kira Radinsky
Though languages can evolve slowly, they can also react strongly to dramatic world events. By studying the connection between words and events, it is possible to identify which eve…
Learning to Focus when Ranking Answers
Dana Sagi, Tzoof Avny, Kira Radinsky +1
One of the main challenges in ranking is embedding the query and document pairs into a joint feature space, which can then be fed to a learning-to-rank algorithm. To achieve this r…
Learning Word Relatedness over Time
Guy D. Rosin, Eytan Adar, Kira Radinsky
Search systems are often focused on providing relevant results for the "now", assuming both corpora and user needs that focus on the present. However, many corpora today reflect si…
Named Entity Disambiguation for Noisy Text
Yotam Eshel, Noam Cohen, Kira Radinsky +3
We address the task of Named Entity Disambiguation (NED) for noisy text. We present WikilinksNED, a large-scale NED dataset of text fragments from the web, which is significantly n…