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L. Ni

13 papers hereh-index 8031.5k citations511 works total

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

author position
  • middle author8
  • last author5

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • cs.LG2
  • q-fin.CP2
same name
  • L. Ni — 2 papers, h 2
  • L. Ni — 1 paper, h 13

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
20172023
most citedGeneralizing from a Few Examples: A Survey on Few-Shot Learning

791 citations · 1.8k across the 13 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

q-fin.CP2023★ 11 cited

Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investment

Saizhuo Wang, Hang Yuan, Leon Zhou +3

One of the most important tasks in quantitative investment research is mining new alphas (effective trading signals or factors). Traditional alpha mining methods, either hand-craft…

cs.CV2023★ 7 cited

MP-Former: Mask-Piloted Transformer for Image Segmentation

Hao Zhang, Feng Li, Huaizhe Xu +4

We present a mask-piloted Transformer which improves masked-attention in Mask2Former for image segmentation. The improvement is based on our observation that Mask2Former suffers fr…

cs.CV2023★ 8 cited

Lite DETR : An Interleaved Multi-Scale Encoder for Efficient DETR

Feng Li, Ailing Zeng, Shilong Liu +4

Recent DEtection TRansformer-based (DETR) models have obtained remarkable performance. Its success cannot be achieved without the re-introduction of multi-scale feature fusion in t…

cs.CV2023★ 1 cited

Closed-Loop Transcription via Convolutional Sparse Coding

Xili Dai, Ke Chen, Shengbang Tong +9

Autoencoding has achieved great empirical success as a framework for learning generative models for natural images. Autoencoders often use generic deep networks as the encoder or d…

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