Search Results for author: Lei Zou

Found 21 papers, 5 papers with code

GAP: Graph-Assisted Prompts for Dialogue-based Medication Recommendation

no code implementations19 May 2025 Jialun Zhong, Yanzeng Li, Sen Hu, Yang Zhang, Teng Xu, Lei Zou

Medication recommendations have become an important task in the healthcare domain, especially in measuring the accuracy and safety of medical dialogue systems (MDS).

Diagnostic Knowledge Graphs

A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Future

1 code implementation12 Apr 2025 Jialun Zhong, Wei Shen, Yanzeng Li, Songyang Gao, Hua Lu, Yicheng Chen, Yang Zhang, Wei Zhou, Jinjie Gu, Lei Zou

Reward Model (RM) has demonstrated impressive potential for enhancing Large Language Models (LLM), as RM can serve as a proxy for human preferences, providing signals to guide LLMs' behavior in various tasks.

Exploiting Prefix-Tree in Structured Output Interfaces for Enhancing Jailbreak Attacking

1 code implementation19 Feb 2025 Yanzeng Li, Yunfan Xiong, Jialun Zhong, Jinchao Zhang, Jie zhou, Lei Zou

We investigate LLMs' safety mechanisms and their recent applications, revealing a new threat model targeting structured output interfaces, which enable attackers to manipulate the inner logit during LLM generation, requiring only API access permissions.

Prompt Engineering Safety Alignment

DySpec: Faster Speculative Decoding with Dynamic Token Tree Structure

no code implementations15 Oct 2024 Yunfan Xiong, Ruoyu Zhang, Yanzeng Li, Tianhao Wu, Lei Zou

Under low temperature setting, DySpec can improve the throughput up to 9. 1$\times$ and reduce the latency up to 9. 4$\times$ on Llama2-70B.

MedDiT: A Knowledge-Controlled Diffusion Transformer Framework for Dynamic Medical Image Generation in Virtual Simulated Patient

no code implementations22 Aug 2024 Yanzeng Li, Cheng Zeng, Jinchao Zhang, Jie zhou, Lei Zou

Additionally, a well-tuned Diffusion Transformer (DiT) model is incorporated to generate medical images according to the specified patient attributes in the KG.

Diagnostic Hallucination +4

MMPKUBase: A Comprehensive and High-quality Chinese Multi-modal Knowledge Graph

no code implementations3 Aug 2024 Xuan Yi, Yanzeng Li, Lei Zou

Multi-modal knowledge graphs have emerged as a powerful approach for information representation, combining data from different modalities such as text, images, and videos.

Attribute Contrastive Learning +5

Leveraging Large Language Model as Simulated Patients for Clinical Education

no code implementations13 Apr 2024 Yanzeng Li, Cheng Zeng, Jialun Zhong, Ruoyu Zhang, Minhao Zhang, Lei Zou

Simulated Patients (SPs) play a crucial role in clinical medical education by providing realistic scenarios for student practice.

Diagnostic Language Modeling +2

LLMaAA: Making Large Language Models as Active Annotators

1 code implementation30 Oct 2023 Ruoyu Zhang, Yanzeng Li, Yongliang Ma, Ming Zhou, Lei Zou

Recently, the superior few-shot performance of large language models (LLMs) has propelled the development of dataset generation, where the training data are solely synthesized from LLMs.

Active Learning Dataset Generation +3

ADMUS: A Progressive Question Answering Framework Adaptable to Multiple Knowledge Sources

no code implementations9 Aug 2023 Yirui Zhan, Yanzeng Li, Minhao Zhang, Lei Zou

With the introduction of deep learning models, semantic parsingbased knowledge base question answering (KBQA) systems have achieved high performance in handling complex questions.

Knowledge Base Question Answering

TopoBERT: Plug and Play Toponym Recognition Module Harnessing Fine-tuned BERT

no code implementations31 Jan 2023 Bing Zhou, Lei Zou, Yingjie Hu, Yi Qiang, Daniel Goldberg

Extracting precise geographical information from textual contents is crucial in a plethora of applications.

Humanitarian Toponym Recognition

VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene Graph

1 code implementation7 Sep 2022 Yanzeng Li, Zilong Zheng, Wenjuan Han, Lei Zou

Semantic Web technology has successfully facilitated many RDF models with rich data representation methods.

Relational Reasoning Semantic Similarity +1

gBuilder: A Scalable Knowledge Graph Construction System for Unstructured Corpus

no code implementations20 Aug 2022 Yanzeng Li, Lei Zou

Furthermore, we also design a cloud-based self-adaptive task scheduling for gBuilder to ensure its scalability on large-scale knowledge graph construction.

graph construction Scheduling

Crake: Causal-Enhanced Table-Filler for Question Answering over Large Scale Knowledge Base

1 code implementation Findings (NAACL) 2022 Minhao Zhang, Ruoyu Zhang, Yanzeng Li, Lei Zou

Semantic parsing solves knowledge base (KB) question answering (KBQA) by composing a KB query, which generally involves node extraction (NE) and graph composition (GC) to detect and connect related nodes in a query.

Question Answering Relation Extraction +1

NAMER: A Node-Based Multitasking Framework for Multi-Hop Knowledge Base Question Answering

no code implementations NAACL 2021 Minhao Zhang, Ruoyu Zhang, Lei Zou, Yinnian Lin, Sen Hu

We present NAMER, an open-domain Chinese knowledge base question answering system based on a novel node-based framework that better grasps the structural mapping between questions and KB queries by aligning the nodes in a query with their corresponding mentions in question.

Data Augmentation Knowledge Base Question Answering

Sensing population distribution from satellite imagery via deep learning: model selection, neighboring effect, and systematic biases

no code implementations3 Mar 2021 Xiao Huang, Di Zhu, Fan Zhang, Tao Liu, Xiao Li, Lei Zou

The rapid development of remote sensing techniques provides rich, large-coverage, and high-temporal information of the ground, which can be coupled with the emerging deep learning approaches that enable latent features and hidden geographical patterns to be extracted.

All Deep Learning +1

A State-transition Framework to Answer Complex Questions over Knowledge Base

no code implementations EMNLP 2018 Sen Hu, Lei Zou, Xinbo Zhang

Although natural language question answering over knowledge graphs have been studied in the literature, existing methods have some limitations in answering complex questions.

Knowledge Graphs Question Answering

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