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researcher

Huiqiang Jiang

Microsoft Research Asia

42 papers hereh-index 182.3k citations53 works total

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

author position
  • first author5
  • middle author35

Across the 40 of 42 papers where every author was matched, so the position is known.

fields
  • cs.CL23
  • cs.LG11
  • cs.CV5
  • cs.CR1
  • cs.DC1
  • eess.AS1
affiliations
  • Microsoft Research Asia
Homepage
same name
  • Huiqiang Jiang — 4 papers, h 7

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
20212026
most citedLongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression

13 citations · 49 across the 39 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022

Attentive Mask CLIP

Yifan Yang, Weiquan Huang, Yixuan Wei +8

Image token removal is an efficient augmentation strategy for reducing the cost of computing image features. However, this efficient augmentation strategy has been found to adverse…

cs.CL2022

Multi-Level Knowledge Distillation for Out-of-Distribution Detection in Text

Qianhui Wu, Huiqiang Jiang, Haonan Yin +2

Self-supervised representation learning has proved to be a valuable component for out-of-distribution (OoD) detection with only the texts of in-distribution (ID) examples. These ap…

eess.AS2022

Improving Hypernasality Estimation with Automatic Speech Recognition in Cleft Palate Speech

Kaitao Song, Teng Wan, Bixia Wang +9

Hypernasality is an abnormal resonance in human speech production, especially in patients with craniofacial anomalies such as cleft palate. In clinical application, hypernasality e…

cs.CL2022

Decomposed Meta-Learning for Few-Shot Named Entity Recognition

Tingting Ma, Huiqiang Jiang, Qianhui Wu +2

Few-shot named entity recognition (NER) systems aim at recognizing novel-class named entities based on only a few labeled examples. In this paper, we present a decomposed meta-lear…

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