Search Results for author: Ziheng Zhang

Found 22 papers, 16 papers with code

Is a 3D-Tokenized LLM the Key to Reliable Autonomous Driving?

no code implementations28 May 2024 Yifan Bai, Dongming Wu, Yingfei Liu, Fan Jia, Weixin Mao, Ziheng Zhang, Yucheng Zhao, Jianbing Shen, Xing Wei, Tiancai Wang, Xiangyu Zhang

Despite its simplicity, Atlas demonstrates superior performance in both 3D detection and ego planning tasks on nuScenes dataset, proving that 3D-tokenized LLM is the key to reliable autonomous driving.

3D Object Detection Autonomous Driving +4

Multi-perspective Improvement of Knowledge Graph Completion with Large Language Models

1 code implementation4 Mar 2024 Derong Xu, Ziheng Zhang, Zhenxi Lin, Xian Wu, Zhihong Zhu, Tong Xu, Xiangyu Zhao, Yefeng Zheng, Enhong Chen

Knowledge graph completion (KGC) is a widely used method to tackle incompleteness in knowledge graphs (KGs) by making predictions for missing links.

Link Prediction Relation

Editing Factual Knowledge and Explanatory Ability of Medical Large Language Models

1 code implementation28 Feb 2024 Derong Xu, Ziheng Zhang, Zhihong Zhu, Zhenxi Lin, Qidong Liu, Xian Wu, Tong Xu, Wanyu Wang, Yuyang Ye, Xiangyu Zhao, Yefeng Zheng, Enhong Chen

To evaluate the editing impact on the behaviours of LLMs, we propose two model editing studies for medical domain: (1) editing factual knowledge for medical specialization and (2) editing the explanatory ability for complex knowledge.

Benchmarking Hallucination +1

Biomedical Entity Linking as Multiple Choice Question Answering

1 code implementation23 Feb 2024 Zhenxi Lin, Ziheng Zhang, Xian Wu, Yefeng Zheng

Although biomedical entity linking (BioEL) has made significant progress with pre-trained language models, challenges still exist for fine-grained and long-tailed entities.

Entity Linking Multiple-choice +1

Improving Biomedical Entity Linking with Retrieval-enhanced Learning

1 code implementation15 Dec 2023 Zhenxi Lin, Ziheng Zhang, Xian Wu, Yefeng Zheng

Biomedical entity linking (BioEL) has achieved remarkable progress with the help of pre-trained language models.

Contrastive Learning Entity Linking +1

Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network

1 code implementation15 Nov 2023 Yongqi Zhang, Quanming Yao, Ling Yue, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng

Accurately predicting drug-drug interactions (DDI) for emerging drugs, which offer possibilities for treating and alleviating diseases, with computational methods can improve patient care and contribute to efficient drug development.

Graph Neural Network

Relation-aware Ensemble Learning for Knowledge Graph Embedding

2 code implementations13 Oct 2023 Ling Yue, Yongqi Zhang, Quanming Yao, Yong Li, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng

Knowledge graph (KG) embedding is a fundamental task in natural language processing, and various methods have been proposed to explore semantic patterns in distinctive ways.

Ensemble Learning Knowledge Graph Embedding +1

Intelligent Omni Surfaces assisted Integrated Multi Target Sensing and Multi User MIMO Communications

no code implementations13 Jul 2023 Ziheng Zhang, Wen Chen, Qingqing Wu, Zhendong Li, Xusheng Zhu, Jinhong Yuan

Drawing inspiration from the advantages of intelligent reflecting surfaces (IRS) in wireless networks, this paper presents a novel design for intelligent omni surface (IOS) enabled integrated sensing and communications (ISAC).

Robust Sum-Rate Maximization in Transmissive RMS Transceiver-Enabled SWIPT Networks

no code implementations10 Dec 2022 Zhendong Li, Wen Chen, Ziheng Zhang, Qingqing Wu, Huanqing Cao, Jun Li

Since the coupling of optimization variables, the whole optimization problem is non-convex and cannot be solved directly.

Prompt Combines Paraphrase: Teaching Pre-trained Models to Understand Rare Biomedical Words

1 code implementation COLING 2022 Haochun Wang, Chi Liu, Nuwa Xi, Sendong Zhao, Meizhi Ju, Shiwei Zhang, Ziheng Zhang, Yefeng Zheng, Bing Qin, Ting Liu

Prompt-based fine-tuning for pre-trained models has proven effective for many natural language processing tasks under few-shot settings in general domain.

Natural Language Inference

Multi-modal Contrastive Representation Learning for Entity Alignment

1 code implementation COLING 2022 Zhenxi Lin, Ziheng Zhang, Meng Wang, Yinghui Shi, Xian Wu, Yefeng Zheng

Multi-modal entity alignment aims to identify equivalent entities between two different multi-modal knowledge graphs, which consist of structural triples and images associated with entities.

Ranked #2 on Multi-modal Entity Alignment on UMVM-oea-d-w-v1 (using extra training data)

Contrastive Learning Knowledge Graphs +2

PRASEMap: A Probabilistic Reasoning and Semantic Embedding based Knowledge Graph Alignment System

1 code implementation16 Jun 2021 Zhiyuan Qi, Ziheng Zhang, Jiaoyan Chen, Xi Chen, Yefeng Zheng

Knowledge Graph (KG) alignment aims at finding equivalent entities and relations (i. e., mappings) between two KGs.

Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embedding

1 code implementation12 May 2021 Zhiyuan Qi, Ziheng Zhang, Jiaoyan Chen, Xi Chen, Yuejia Xiang, Ningyu Zhang, Yefeng Zheng

Knowledge Graph (KG) alignment is to discover the mappings (i. e., equivalent entities, relations, and others) between two KGs.

An Industry Evaluation of Embedding-based Entity Alignment

1 code implementation COLING 2020 Ziheng Zhang, Jiaoyan Chen, Xi Chen, Hualuo Liu, Yuejia Xiang, Bo Liu, Yefeng Zheng

Embedding-based entity alignment has been widely investigated in recent years, but most proposed methods still rely on an ideal supervised learning setting with a large number of unbiased seed mappings for training and validation, which significantly limits their usage.

Entity Alignment Knowledge Graphs

Learning Semantics-aware Distance Map with Semantics Layering Network for Amodal Instance Segmentation

1 code implementation30 May 2019 Ziheng Zhang, Anpei Chen, Ling Xie, Jingyi Yu, Shenghua Gao

Specifically, we first introduce a new representation, namely a semantics-aware distance map (sem-dist map), to serve as our target for amodal segmentation instead of the commonly used masks and heatmaps.

Amodal Instance Segmentation Segmentation +1

Photo-Realistic Facial Details Synthesis from Single Image

1 code implementation ICCV 2019 Anpei Chen, Zhang Chen, Guli Zhang, Ziheng Zhang, Kenny Mitchell, Jingyi Yu

Our technique employs expression analysis for proxy face geometry generation and combines supervised and unsupervised learning for facial detail synthesis.

Face Generation

Saliency Detection in 360° Videos

no code implementations ECCV 2018 Ziheng Zhang, Yanyu Xu, Jingyi Yu, Shenghua Gao

Considering that the 360° videos are usually stored with equirectangular panorama, we propose to implement the spherical convolution on panorama by stretching and rotating the kernel based on the location of patch to be convolved.

Video Saliency Detection

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