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Hannaneh Hajishirzi

134 papers hereh-index 8344.1k citations195 works total

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

author position
  • first author3
  • middle author60
  • last author67

Across the 130 of 134 papers where every author was matched, so the position is known.

fields
  • cs.CL103
  • cs.CV13
  • cs.LG7
  • cs.AI5
  • cs.IR3
  • cs.DB1
same name
  • Hannaneh Hajishirzi — 6 papers
  • Hannaneh Hajishirzi — 1 paper

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
20122026
most citedBidirectional Attention Flow for Machine Comprehension

1.6k citations · 4.5k across the 123 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

cs.CV2017★ 4 cited

Identifying Most Walkable Direction for Navigation in an Outdoor Environment

Sachin Mehta, Hannaneh Hajishirzi, Linda Shapiro

We present an approach for identifying the most walkable direction for navigation using a hand-held camera. Our approach extracts semantically rich contextual information from the…

cs.CL2017★ 66 cited

Neural Speed Reading via Skim-RNN

Minjoon Seo, Sewon Min, Ali Farhadi +1

Inspired by the principles of speed reading, we introduce Skim-RNN, a recurrent neural network (RNN) that dynamically decides to update only a small fraction of the hidden state fo…

cs.CL2017★ 9 cited

Scientific Information Extraction with Semi-supervised Neural Tagging

Yi Luan, Mari Ostendorf, Hannaneh Hajishirzi

This paper addresses the problem of extracting keyphrases from scientific articles and categorizing them as corresponding to a task, process, or material. We cast the problem as se…

cs.CL2017★ 18 cited

Question Answering through Transfer Learning from Large Fine-grained Supervision Data

Sewon Min, Minjoon Seo, Hannaneh Hajishirzi

We show that the task of question answering (QA) can significantly benefit from the transfer learning of models trained on a different large, fine-grained QA dataset. We achieve th…

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