Search Results for author: Sijia Chen

Found 15 papers, 4 papers with code

Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees

no code implementations11 Jun 2024 Sijia Chen, Yibo Wang, Yi-Feng Wu, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Lijun Zhang

In this study, we propose an inference trajectory optimization framework based on the preference data extracted from decision trees to address this limitation.

Delving into the Trajectory Long-tail Distribution for Muti-object Tracking

1 code implementation CVPR 2024 Sijia Chen, En Yu, Jinyang Li, Wenbing Tao

In this study, we pioneer an exploration into the distribution patterns of tracking data and identify a pronounced long-tail distribution issue within existing MOT datasets.

Data Augmentation Multiple Object Tracking +1

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models

no code implementations17 Feb 2024 Sijia Chen, Baochun Li, Di Niu

The reasoning performance of Large Language Models (LLMs) on a wide range of problems critically relies on chain-of-thought prompting, which involves providing a few chain of thought demonstrations as exemplars in prompts.

Language-Guided Diffusion Model for Visual Grounding

1 code implementation18 Aug 2023 Sijia Chen, Baochun Li

Specifically, we propose a language-guided diffusion framework for visual grounding, LG-DVG, which trains the model to progressively reason queried object boxes by denoising a set of noisy boxes with the language guide.

cross-modal alignment Denoising +1

Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization

no code implementations9 Feb 2023 Sijia Chen, Yu-Jie Zhang, Wei-Wei Tu, Peng Zhao, Lijun Zhang

Inspired by their work, we investigate the theoretical guarantees of optimistic online mirror descent (OMD) for the SEA model.

Multi-Modal Dynamic Graph Transformer for Visual Grounding

1 code implementation CVPR 2022 Sijia Chen, Baochun Li

We found that existing VG methods are trapped by the single-stage grounding process that performs a sole evaluate-and- rank for meticulously prepared regions.

Visual Grounding

Towards Generalizable Personalized Federated Learning with Adaptive Local Adaptation

no code implementations29 Sep 2021 Sijia Chen, Baochun Li

In this paper, we point out that this issue can be addressed by balancing information flow from the initial model and training dataset to the local adaptation.

Meta-Learning Personalized Federated Learning

Ammonia-induced Calcium Phosphate Nanostructure: A Potential Assay for Studying Osteoporosis and Bone Metastasis

no code implementations9 Apr 2021 Sijia Chen, Qiong Wang, Felipe Eltit, Yubin Guo, Michael Cox, Rizhi Wang

To demon-strate the application in studying bone metastasis, we delivered PC3 prostate cancer conditioned medium and confirmed that both the differentiation of monocytes into osteoclasts and the osteoclastic resorption of the calcium phosphate coating were significantly enhanced.

Cultural Vocal Bursts Intensity Prediction

An Optimized H.266/VVC Software Decoder On Mobile Platform

no code implementations5 Mar 2021 Yiming Li, Shan Liu, Yu Chen, Yushan Zheng, Sijia Chen, Bin Zhu, Jian Lou

As the successor of H. 265/HEVC, the new versatile video coding standard (H. 266/VVC) can provide up to 50% bitrate saving with the same subjective quality, at the cost of increased decoding complexity.

4k Decoder

1st Place Solutions for Waymo Open Dataset Challenges -- 2D and 3D Tracking

no code implementations28 Jun 2020 Yu Wang, Sijia Chen, Li Huang, Runzhou Ge, Yihan Hu, Zhuangzhuang Ding, Jie Liao

This technical report presents the online and real-time 2D and 3D multi-object tracking (MOT) algorithms that reached the 1st places on both Waymo Open Dataset 2D tracking and 3D tracking challenges.

3D Multi-Object Tracking

1st Place Solution for Waymo Open Dataset Challenge -- 3D Detection and Domain Adaptation

no code implementations28 Jun 2020 Zhuangzhuang Ding, Yihan Hu, Runzhou Ge, Li Huang, Sijia Chen, Yu Wang, Jie Liao

We proposed a one-stage, anchor-free and NMS-free 3D point cloud object detector AFDet, using object key-points to encode the 3D attributes, and to learn an end-to-end point cloud object detection without the need of hand-engineering or learning the anchors.

Domain Adaptation Object +2

AFDet: Anchor Free One Stage 3D Object Detection

6 code implementations23 Jun 2020 Runzhou Ge, Zhuangzhuang Ding, Yihan Hu, Yu Wang, Sijia Chen, Li Huang, Yuan Li

High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving.

3D Object Detection Autonomous Driving +2

Structured Bayesian Compression for Deep models in mobile enabled devices for connected healthcare

no code implementations13 Feb 2019 Sijia Chen, Bin Song, Xiaojiang Du, Nadra Guizani

Deep Models, typically Deep neural networks, have millions of parameters, analyze medical data accurately, yet in a time-consuming method.

Computational Efficiency

FPAN: Fine-grained and Progressive Attention Localization Network for Data Retrieval

no code implementations5 Apr 2018 Sijia Chen, Bin Song, Jie Guo, Xiaojiang Du, Mohsen Guizani

The Localization of the target object for data retrieval is a key issue in the Intelligent and Connected Transportation Systems (ICTS).

Multi-Task Learning Object +3

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