Wei Ye

Graph Neural Diffusion Networks for Semi-supervised Learning

2022 · arXiv (Cornell University)

Graph Convolutional Networks (GCN) is a pioneering model for graph-based semi-supervised learning. However, GCN does not perform well on sparsely-labeled graphs. Its two-layer version cannot effectively propagate the label information to the whole graph structure …

Hal-Eval: A Universal and Fine-grained Hallucination Evaluation Framework for Large Vision Language Models

2024 · arXiv (Cornell University)

Large Vision Language Models exhibit remarkable capabilities but struggle with hallucinations inconsistencies between images and their descriptions. Previous hallucination evaluation studies on LVLMs have identified hallucinations in terms of objects, attributes, and relations but overlooked …

Labels Need Prompts Too: Mask Matching for Natural Language Understanding Tasks

2024 · Proceedings of the AAAI Conference on Artificial Intelligence

Textual label names (descriptions) are typically semantically rich in many natural language understanding (NLU) tasks. In this paper, we incorporate the prompting methodology, which is widely used to enrich model input, into the label side …

RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation

2024 · arXiv (Cornell University)

Large Language Models (LLMs) demonstrate human-level capabilities in dialogue, reasoning, and knowledge retention. However, even the most advanced LLMs face challenges such as hallucinations and real-time updating of their knowledge. Current research addresses this bottleneck …

Distributional Shortest-Path Graph Kernels

2025 · IEEE Transactions on Knowledge and Data Engineering

Traditional shortest-path graph kernels generate for each graph a histogram-like feature map, whose elements represent the number of occurrences of non-isomorphic shortest paths in this graph. The histogram-like feature map does not contain the distributions …

A Survey on Evaluation of Large Language Models

2024 · ACM Transactions on Intelligent Systems and Technology

Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, …