HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.251 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, Christopher D. Manning. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 2018.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Topic
- Topic Modeling
- Field
- Computer Science
- Canadian institutions
- Université de Montréal
- Funders
- Office of Naval ResearchDefense Advanced Research Projects AgencyUniversité de MontréalNvidiaNational Science Foundation
- Keywords
- ZhàngQuestion answeringComputer scienceArtificial intelligenceNatural language processingInformation retrievalHistoryChinaArchaeology
- Has abstract in OpenAlex
- yes