Zhang, Wei

Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning

2019 · Zurich Open Repository and Archive (University of Zurich)

Reasoning is essential for the development of large knowledge graphs, especially for completion, which aims to infer new triples based on existing ones. Both rules and embeddings can be used for knowledge graph reasoning and …

PDT: Pretrained Dual Transformers for Time-aware Bipartite Graphs

2023 · arXiv (Cornell University)

Pre-training on large models is prevalent and emerging with the ever-growing user-generated content in many machine learning application categories. It has been recognized that learning contextual knowledge from the datasets depicting user-content interaction plays a …

Don't Forget Your Reward Values: Language Model Alignment via Value-based Calibration

2024 · arXiv (Cornell University)

While Reinforcement Learning from Human Feedback (RLHF) significantly enhances the generation quality of Large Language Models (LLMs), recent studies have raised concerns regarding the complexity and instability associated with the Proximal Policy Optimization (PPO) algorithm, …