Publications | Pengcheng Wang

ECCV

Look Less, Think Faster: Joint Token-Compute Adaptation for Multimodal LLMs

Pengcheng Wang, Zhiquan Wang, Jayoung Lee, Zhuoyan Xu, Ran Xu, Saurabh Bagchi, Yin Li, and Somali Chaterji

In Proceedings of the European Conference on Computer Vision, 2026

@inproceedings{wang2026smartvl,
  title = {Look Less, Think Faster: Joint Token-Compute Adaptation for Multimodal LLMs},
  author = {Wang, Pengcheng and Wang, Zhiquan and Lee, Jayoung and Xu, Zhuoyan and Xu, Ran and Bagchi, Saurabh and Li, Yin and Chaterji, Somali},
  booktitle = {Proceedings of the European Conference on Computer Vision},
  year = {2026},
}

MobiSys
Agile3D: Adaptive Contention- and Content-Aware 3D Object Detection for Embedded GPUs

Pengcheng Wang, Zhuoming Liu, Shayok Bagchi, Ran Xu, Saurabh Bagchi, Yin Li, and Somali Chaterji

In Proceedings of the 23rd ACM International Conference on Mobile Systems, Applications, and Services, 2025

Abstract Bib PDF Video Code Poster

Agile3D is an adaptive 3D object detection system for embedded GPUs. It integrates a cross-model multi-branch execution framework with a contention- and content-aware reinforcement learning controller to dynamically balance detection accuracy and inference latency under changing input scenes and hardware contention.
@inproceedings{wang2025agile3d, title = {Agile3D: Adaptive Contention- and Content-Aware 3D Object Detection for Embedded GPUs}, author = {Wang, Pengcheng and Liu, Zhuoming and Bagchi, Shayok and Xu, Ran and Bagchi, Saurabh and Li, Yin and Chaterji, Somali}, booktitle = {Proceedings of the 23rd ACM International Conference on Mobile Systems, Applications, and Services}, year = {2025}, publisher = {ACM}, }
TODAES
Virtuoso: Energy- and Latency-Aware Streamlining of Streaming Videos on SOCs

Jayoung Lee, Pengcheng Wang, Ran Xu, Sarthak Jain, Venkat Dasari, Noah Weston, Yin Li, Saurabh Bagchi, and Somali Chaterji

ACM Transactions on Design Automation of Electronic Systems, 2023

Abstract DOI Bib

Virtuoso is an efficient and adaptive video object detection system that jointly optimizes accuracy, energy efficiency, and latency on system-on-chips. It uses a multi-branch execution kernel and a lightweight runtime scheduler to select operating points across the accuracy-energy-latency space.
@article{lee2023virtuoso, title = {Virtuoso: Energy- and Latency-Aware Streamlining of Streaming Videos on SOCs}, author = {Lee, Jayoung and Wang, Pengcheng and Xu, Ran and Jain, Sarthak and Dasari, Venkat and Weston, Noah and Li, Yin and Bagchi, Saurabh and Chaterji, Somali}, journal = {ACM Transactions on Design Automation of Electronic Systems}, year = {2023}, publisher = {ACM}, doi = {10.1145/3564289}, }
EuroSys
LiteReconfig: Cost and Content Aware Reconfiguration of Video Object Detection Systems for Mobile GPUs

Ran Xu, Jayoung Lee, Pengcheng Wang, Saurabh Bagchi, Yin Li, and Somali Chaterji

In Proceedings of the European Conference on Computer Systems, 2022

Abstract DOI Bib

LiteReconfig is an efficient adaptive video object detection framework for mobile GPUs. It uses a cost-benefit analyzer and a content-aware accuracy prediction model to decide which features to evaluate and which execution branch to run at inference time.
@inproceedings{xu2022litereconfig, title = {LiteReconfig: Cost and Content Aware Reconfiguration of Video Object Detection Systems for Mobile GPUs}, author = {Xu, Ran and Lee, Jayoung and Wang, Pengcheng and Bagchi, Saurabh and Li, Yin and Chaterji, Somali}, booktitle = {Proceedings of the European Conference on Computer Systems}, year = {2022}, publisher = {ACM}, doi = {10.1145/3492321.3519577}, }
TOSN
ApproxNet: Content and Contention-Aware Video Object Classification System for Embedded Clients

Ran Xu, Rakesh Kumar, Pengcheng Wang, Peter Bai, Ganga Meghanath, Somali Chaterji, Subrata Mitra, and Saurabh Bagchi

ACM Transactions on Sensor Networks, 2022

Abstract DOI Bib

ApproxNet is a video object classification system for embedded and mobile clients. It enables runtime approximation within a single neural network to meet latency and accuracy trade-offs under changing content, resource contention, and user requirements.
@article{xu2022approxnet, title = {ApproxNet: Content and Contention-Aware Video Object Classification System for Embedded Clients}, author = {Xu, Ran and Kumar, Rakesh and Wang, Pengcheng and Bai, Peter and Meghanath, Ganga and Chaterji, Somali and Mitra, Subrata and Bagchi, Saurabh}, journal = {ACM Transactions on Sensor Networks}, year = {2022}, publisher = {ACM}, doi = {10.1145/3463530}, }
SenSys
ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles

Ran Xu, Chen-lin Zhang, Pengcheng Wang, Jayoung Lee, Subrata Mitra, Somali Chaterji, Yin Li, and Saurabh Bagchi

In Proceedings of the ACM Conference on Embedded Networked Sensor Systems, 2020

Abstract DOI Bib

ApproxDet is an adaptive video object detection framework for mobile devices. It dynamically selects execution branches to meet accuracy-latency objectives under changing video content, compute contention, and user requirements.
@inproceedings{xu2020approxdet, title = {ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles}, author = {Xu, Ran and Zhang, Chen-lin and Wang, Pengcheng and Lee, Jayoung and Mitra, Subrata and Chaterji, Somali and Li, Yin and Bagchi, Saurabh}, booktitle = {Proceedings of the ACM Conference on Embedded Networked Sensor Systems}, year = {2020}, publisher = {ACM}, doi = {10.1145/3384419.3431159}, }