76 citations · 90 across the 11 of their papers we have counts for
11 papers
Modality Equilibrium Matters: Minor-Modality-Aware Adaptive Alternating for Cross-Modal Memory Enhancement
Xiang Shi, Rui Zhang, Jiawei Liu +3
Multimodal fusion is susceptible to modality imbalance, where dominant modalities overshadow weak ones, easily leading to biased learning and suboptimal fusion, especially for inco…
FlippedRAG: Black-Box Opinion Manipulation Adversarial Attacks to Retrieval-Augmented Generation Models
Zhuo Chen, Yuyang Gong, Jiawei Liu +6
Retrieval-Augmented Generation (RAG) enriches LLMs by dynamically retrieving external knowledge, reducing hallucinations and satisfying real-time information needs. While existing…
Every Part Matters: Integrity Verification of Scientific Figures Based on Multimodal Large Language Models
Xiang Shi, Jiawei Liu, Yinpeng Liu +2
This paper tackles a key issue in the interpretation of scientific figures: the fine-grained alignment of text and figures. It advances beyond prior research that primarily dealt w…
Black-Box Opinion Manipulation Attacks to Retrieval-Augmented Generation of Large Language Models
Zhuo Chen, Jiawei Liu, Haotan Liu +4
Retrieval-Augmented Generation (RAG) is applied to solve hallucination problems and real-time constraints of large language models, but it also induces vulnerabilities against retr…
From Model-centered to Human-Centered: Revision Distance as a Metric for Text Evaluation in LLMs-based Applications
Yongqiang Ma, Lizhi Qing, Jiawei Liu +5
Evaluating large language models (LLMs) is fundamental, particularly in the context of practical applications. Conventional evaluation methods, typically designed primarily for LLM…
Let's Learn Step by Step: Enhancing In-Context Learning Ability with Curriculum Learning
Yinpeng Liu, Jiawei Liu, Xiang Shi +3
Demonstration ordering, which is an important strategy for in-context learning (ICL), can significantly affects the performance of large language models (LLMs). However, most of th…
Know Where to Go: Make LLM a Relevant, Responsible, and Trustworthy Searcher
Xiang Shi, Jiawei Liu, Yinpeng Liu +2
The advent of Large Language Models (LLMs) has shown the potential to improve relevance and provide direct answers in web searches. However, challenges arise in validating the reli…
Low-Resource Multi-Granularity Academic Function Recognition Based on Multiple Prompt Knowledge
Jiawei Liu, Zi Xiong, Yi Jiang +4
Fine-tuning pre-trained language models (PLMs), e.g., SciBERT, generally requires large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in…
AI vs. Human -- Differentiation Analysis of Scientific Content Generation
Yongqiang Ma, Jiawei Liu, Fan Yi +4
Recent neural language models have taken a significant step forward in producing remarkably controllable, fluent, and grammatical text. Although studies have found that AI-generate…
Predicting the clinical citation count of biomedical papers using multilayer perceptron neural network
Xin Li, Xuli Tang, Qikai Cheng
The number of clinical citations received from clinical guidelines or clinical trials has been considered as one of the most appropriate indicators for quantifying the clinical imp…
Fixed versus Dynamic Co-Occurrence Windows in TextRank Term Weights for Information Retrieval
Wei Lu, Qikai Cheng, Christina Lioma
TextRank is a variant of PageRank typically used in graphs that represent documents, and where vertices denote terms and edges denote relations between terms. Quite often the relat…