activity
20192022
most citedOverview of the TREC 2020 deep learning track

117 citations · 217 across the 10 of their papers we have counts for

collaborators

13 papers

cs.CL2022

Compressing Cross-Lingual Multi-Task Models at Qualtrics

Daniel Campos, Daniel Perry, Samir Joshi +4

Experience management is an emerging business area where organizations focus on understanding the feedback of customers and employees in order to improve their end-to-end experienc…

q-bio.QM20219 cited

IMG2SMI: Translating Molecular Structure Images to Simplified Molecular-input Line-entry System

Daniel Campos, Heng Ji

Like many scientific fields, new chemistry literature has grown at a staggering pace, with thousands of papers released every month. A large portion of chemistry literature focuses…

cs.CL202114 cited

Curriculum learning for language modeling

Daniel Campos

Language Models like ELMo and BERT have provided robust representations of natural language, which serve as the language understanding component for a diverse range of downstream t…

cs.IR2021

MS MARCO: Benchmarking Ranking Models in the Large-Data Regime

Nick Craswell, Bhaskar Mitra, Emine Yilmaz +2

Evaluation efforts such as TREC, CLEF, NTCIR and FIRE, alongside public leaderboard such as MS MARCO, are intended to encourage research and track our progress, addressing big ques…

cs.IR20211 cited

TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime

Nick Craswell, Bhaskar Mitra, Emine Yilmaz +3

The TREC Deep Learning (DL) Track studies ad hoc search in the large data regime, meaning that a large set of human-labeled training data is available. Results so far indicate that…

cs.IR20215 cited

Significant Improvements over the State of the Art? A Case Study of the MS MARCO Document Ranking Leaderboard

Jimmy Lin, Daniel Campos, Nick Craswell +2

Leaderboards are a ubiquitous part of modern research in applied machine learning. By design, they sort entries into some linear order, where the top-scoring entry is recognized as…