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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 2025Show all

3 papers · 1 filter

cs.CL2025

Do Activation Verbalization Methods Convey Privileged Information?

Millicent Li, Alberto Mario Ceballos Arroyo, Giordano Rogers +2

Recent interpretability methods have proposed to translate LLM internal representations into natural language descriptions using a second verbalizer LLM. This is intended to illumi…

cs.LG2025

Can Interpretation Predict Behavior on Unseen Data?

Victoria R. Li, Jenny Kaufmann, Tian Qin +3

Interpretability research often predicts model responses to targeted mechanistic interventions. But can we predict responses to unseen input data? We propose and demonstrate this a…

cs.CL2025

PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs

Oskar van der Wal, Pietro Lesci, Max Muller-Eberstein +4

The stability of language model pre-training and its effects on downstream performance are still understudied. Prior work shows that the training process can yield significantly di…

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