Tengjin Weng

Tengjin Weng

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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

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Blog Post number 4

less than 1 minute read

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

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Blog Post number 2

less than 1 minute read

Published:

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Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

Accurate Segmentation of Optic Disc and Cup from Multiple Pseudo-labels by Noise-aware Learning

Published in IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2024

A noise-aware learning method for optic disc and cup segmentation from multiple pseudo-labels.

Recommended citation: Weng, Tengjin, Yang Shen, Zhidong Zhao, Zhiming Cheng, and Shuai Wang. (2024). "Accurate Segmentation of Optic Disc and Cup from Multiple Pseudo-labels by Noise-aware Learning." CSCWD.
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Enhancing point annotations with superpixel and confident learning guided for improving semi-supervised OCT fluid segmentation

Published in Biomedical Signal Processing and Control, 2024

A semi-supervised OCT fluid segmentation method using point annotations, superpixels, and confident learning.

Recommended citation: Weng, Tengjin, Yang Shen, Kai Jin, Yaqi Wang, Zhiming Cheng, Yunxiang Li, Gewen Zhang, and Shuai Wang. (2024). "Enhancing point annotations with superpixel and confident learning guided for improving semi-supervised OCT fluid segmentation." Biomedical Signal Processing and Control.
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LlamaSeg: Image Segmentation via Autoregressive Mask Generation

Published in Submitted to ICLR 2026, 2025

A visual autoregressive framework that unifies image segmentation tasks through natural language instructions.

Recommended citation: Deng, Jiru, Tengjin Weng, Tianyu Yang, Wenhan Luo, Zhiheng Li, and Wenhao Jiang. (2025). "LlamaSeg: Image Segmentation via Autoregressive Mask Generation." Submitted to ICLR 2026.
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VisNumBench: Evaluating Number Sense of Multimodal Large Language Models

Published in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2025

A benchmark for evaluating visual number sense in multimodal large language models.

Recommended citation: Weng, Tengjin, Jingyi Wang, Wenhao Jiang, and Zhong Ming. (2025). "VisNumBench: Evaluating Number Sense of Multimodal Large Language Models." Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 3830-3840.
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Multi-annotation agreement and prediction consistency networks: Improving semi-supervised segmentation of medical images with ambiguous boundaries

Published in Artificial Intelligence in Medicine, 2026

Co-first author. Semi-supervised medical image segmentation with ambiguous boundaries and multi-annotated data.

Recommended citation: Wang, Shuai*, Tengjin Weng*, Jingyi Wang, Kai Zhao, Yang Shen, Zhidong Zhao, Yixiu Liu, Pengfei Jiao, Zhiming Cheng, Yaoqi Sun, and Yaqi Wang. (2026). "Multi-annotation agreement and prediction consistency networks: Improving semi-supervised segmentation of medical images with ambiguous boundaries." Artificial Intelligence in Medicine, 171, 103289. *Equal contribution.
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GRPO-VPS: Enhancing Group Relative Policy Optimization with Verifiable Process Supervision for Effective Reasoning

Published in ICLR 2026 Workshop on LLM Reasoning, 2026

A verifiable process supervision method for improving GRPO credit assignment and reasoning efficiency.

Recommended citation: Wang, Jingyi, Lei Zhu, Tengjin Weng, Song-Li Wu, Haochen Tan, Jierun Chen, Chaofan Tao, Haoli Bai, Lu Hou, Lifeng Shang, and Xiao-Ping Zhang. (2026). "GRPO-VPS: Enhancing Group Relative Policy Optimization with Verifiable Process Supervision for Effective Reasoning." ICLR 2026 Workshop on LLM Reasoning.
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OddGridBench: Exposing the Lack of Fine-Grained Visual Discrepancy Sensitivity in Multimodal Large Language Models

Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Highlight, 2026

CVPR 2026 Highlight. A controllable benchmark for evaluating fine-grained visual discrepancy sensitivity in multimodal large language models.

Recommended citation: Weng, Tengjin, Wenhao Jiang, Jingyi Wang, Ming Li, Lin Ma, and Zhong Ming. (2026). "OddGridBench: Exposing the Lack of Fine-Grained Visual Discrepancy Sensitivity in Multimodal Large Language Models." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Highlight.
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.