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Ming-Wei Chang

33 papers hereh-index 46137.8k citations110 works total

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

author position
  • first author1
  • middle author23
  • last author9

Across the 33 of 33 papers where every author was matched, so the position is known.

fields
  • cs.CL30
  • cs.AI1
  • cs.IR1
  • cs.LG1
same name
  • Ming-Wei Chang — 5 papers, h 5
  • Ming-Wei Chang — 5 papers, h 5
  • Ming-Wei Chang — 3 papers, h 6
  • Ming-Wei Chang — 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

works on
interpretability 1knowledge retrieval 1language model pretraining 1open-domain question answering 1retrieval-augmented models 1

From the 1 of 33 linked papers with an AI index.

activity
20152023
most citedREALM: Retrieval-Augmented Language Model Pre-Training

521 citations · 1.5k across the 28 of their papers we have counts for

collaborators
Showing 2023Show all

3 papers · 1 filter

cs.CL2023

QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations

Chaitanya Malaviya, Peter Shaw, Ming-Wei Chang +2

Formulating selective information needs results in queries that implicitly specify set operations, such as intersection, union, and difference. For instance, one might search for "…

cs.CL2023★ 6 cited

Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference

Tao Lei, Junwen Bai, Siddhartha Brahma +9

We propose Conditional Adapter (CoDA), a parameter-efficient transfer learning method that also improves inference efficiency. CoDA generalizes beyond standard adapter approaches t…

cs.CL2023★ 7 cited

Rethinking the Role of Token Retrieval in Multi-Vector Retrieval

Jinhyuk Lee, Zhuyun Dai, Sai Meher Karthik Duddu +4

Multi-vector retrieval models such as ColBERT [Khattab and Zaharia, 2020] allow token-level interactions between queries and documents, and hence achieve state of the art on many i…

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