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Vikas Chandra

12 papers hereh-index 111.5k citations23 works total

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

author position
  • middle author6
  • last author6

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.LG4
  • cs.CV3
  • cs.DC1
same name
  • Vikas Chandra — 38 papers, h 16
  • Vikas Chandra — 7 papers, h 2
  • Vikas Chandra — 2 papers

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
20172026
most citedMiniGPT-v2: large language model as a unified interface for vision-language multi-task learning

67 citations · 121 across the 12 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022

Fast Point Cloud Generation with Straight Flows

Lemeng Wu, Dilin Wang, Chengyue Gong +6

Diffusion models have emerged as a powerful tool for point cloud generation. A key component that drives the impressive performance for generating high-quality samples from noise i…

cs.CV2022★ 1 cited

PathFusion: Path-consistent Lidar-Camera Deep Feature Fusion

Lemeng Wu, Dilin Wang, Meng Li +4

Fusing 3D LiDAR features with 2D camera features is a promising technique for enhancing the accuracy of 3D detection, thanks to their complementary physical properties. While most…

cs.DC2022

DREAM: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads

Seah Kim, Hyoukjun Kwon, Jinook Song +4

Emerging real-time multi-model ML (RTMM) workloads such as AR/VR and drone control involve dynamic behaviors in various granularity; task, model, and layers within a model. Such dy…

cs.LG2022★ 7 cited

DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks

Yonggan Fu, Haichuan Yang, Jiayi Yuan +5

Efficient deep neural network (DNN) models equipped with compact operators (e.g., depthwise convolutions) have shown great potential in reducing DNNs' theoretical complexity (e.g.,…

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