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researcher

Naomi Saphra

University of Edinburgh

26 papers hereh-index 171.6k citations38 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author16
  • last author5

Across the 25 of 26 papers where every author was matched, so the position is known.

fields
  • cs.CL17
  • cs.LG6
  • astro-ph.IM1
  • cs.DL1
  • stat.ML1
affiliations
  • University of Edinburgh
  • Johns Hopkins University
  • Kempner Institute
  • Harvard University
  • Carnegie Mellon University
  • New York University
Homepage
same name
  • Naomi Saphra — 6 papers, h 3
  • Naomi Saphra — 4 papers, h 2
  • Naomi Saphra — 3 papers, h 1
  • Naomi Saphra — 1 paper
  • Naomi Saphra — 1 paper, h 2
  • Naomi Saphra — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132026
most citedDyNet: The Dynamic Neural Network Toolkit

343 citations · 489 across the 23 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.DL2022★ 1 cited

One Venue, Two Conferences: The Separation of Chinese and American Citation Networks

Bingchen Zhao, Yuling Gu, Jessica Zosa Forde +1

At NeurIPS, American and Chinese institutions cite papers from each other's regions substantially less than they cite endogamously. We build a citation graph to quantify this divid…

cs.CL2022★ 70 cited

State-of-the-art generalisation research in NLP: A taxonomy and review

Dieuwke Hupkes, Mario Giulianelli, Verna Dankers +17

The ability to generalise well is one of the primary desiderata of natural language processing (NLP). Yet, what 'good generalisation' entails and how it should be evaluated is not…

cs.CL2022★ 4 cited

Benchmarking Compositionality with Formal Languages

Josef Valvoda, Naomi Saphra, Jonathan Rawski +2

Recombining known primitive concepts into larger novel combinations is a quintessentially human cognitive capability. Whether large neural models in NLP can acquire this ability wh…

cs.LG2022★ 7 cited

Linear Connectivity Reveals Generalization Strategies

Jeevesh Juneja, Rachit Bansal, Kyunghyun Cho +2

It is widely accepted in the mode connectivity literature that when two neural networks are trained similarly on the same data, they are connected by a path through parameter space…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.