HPC Lab is proud to have five papers accepted at ACM SIGIR 2020, the major international forum for the presentation of new research results in the field of information retrieval (IR). They are on hot research topics including neural IR, conversational search, and learning to rank. Below the references and the links to preprints available on arXiv.

1. “Efficient Document Re-Ranking for Transformers by Precomputing Term Representations”, by Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder. Accepted as a full paper at #SIGIR2020. Preprint available here: http://arxiv.org/abs/2004.14255
2. “Training Curricula for Open Domain Answer Re-Ranking”, by Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder. Accepted as a full paper at #SIGIR2020. Preprint available here: http://arxiv.org/abs/2004.14269
3. “Expansion via Prediction of Importance with Contextualization” by Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder. Accepted as a short paper at #SIGIR2020. Preprint available here: http://arxiv.org/abs/2004.14245
4. “Topic Propagation in Conversational Search” by Ida Mele, Cristina I. Muntean, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Ophir Frieder. Accepted as a short paper at #SIGIR2020. Preprint available here: http://arxiv.org/abs/2004.14054
5. “Query-level Early Exit for Additive Learning-to-Rank Ensembles” by Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Salvatore Trani. Accepted as a short paper at #SIGIR2020. Preprint available here: http://arxiv.org/abs/2004.14641

Do not hesitate to ask the authors for further information!