Search Results for author: Jiaying Lu

Found 14 papers, 7 papers with code

LogicPrpBank: A Corpus for Logical Implication and Equivalence

1 code implementation14 Feb 2024 Zhexiong Liu, Jing Zhang, Jiaying Lu, Wenjing Ma, Joyce C Ho

Logic reasoning has been critically needed in problem-solving and decision-making.

Decision Making

AgentLens: Visual Analysis for Agent Behaviors in LLM-based Autonomous Systems

no code implementations14 Feb 2024 Jiaying Lu, Bo Pan, Jieyi Chen, Yingchaojie Feng, Jingyuan Hu, Yuchen Peng, Wei Chen

Recently, Large Language Model based Autonomous system(LLMAS) has gained great popularity for its potential to simulate complicated behaviors of human societies.

Language Modelling Large Language Model

Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models

1 code implementation1 Jan 2024 Guangji Bai, Zheng Chai, Chen Ling, Shiyu Wang, Jiaying Lu, Nan Zhang, Tingwei Shi, Ziyang Yu, Mengdan Zhu, Yifei Zhang, Carl Yang, Yue Cheng, Liang Zhao

We categorize methods based on their optimization focus: computational, memory, energy, financial, and network resources and their applicability across various stages of an LLM's lifecycle, including architecture design, pretraining, finetuning, and system design.

HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Prompting

no code implementations12 Apr 2023 Jiaying Lu, Jiaming Shen, Bo Xiong, Wenjing Ma, Steffen Staab, Carl Yang

Medical decision-making processes can be enhanced by comprehensive biomedical knowledge bases, which require fusing knowledge graphs constructed from different sources via a uniform index system.

Decision Making Knowledge Graphs

MuG: A Multimodal Classification Benchmark on Game Data with Tabular, Textual, and Visual Fields

1 code implementation6 Feb 2023 Jiaying Lu, Yongchen Qian, Shifan Zhao, Yuanzhe Xi, Carl Yang

Previous research has demonstrated the advantages of integrating data from multiple sources over traditional unimodal data, leading to the emergence of numerous novel multimodal applications.


How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generation

1 code implementation12 Jan 2022 Hejie Cui, Jiaying Lu, Yao Ge, Carl Yang

Graph neural networks (GNNs), as a group of powerful tools for representation learning on irregular data, have manifested superiority in various downstream tasks.

Representation Learning Retrieval

Weakly Supervised Concept Map Generation through Task-Guided Graph Translation

1 code implementation8 Oct 2021 Jiaying Lu, Xiangjue Dong, Carl Yang

Recent years have witnessed the rapid development of concept map generation techniques due to their advantages in providing well-structured summarization of knowledge from free texts.

Document Classification Translation

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