Man Lan

A Learning Error Analysis for Structured Prediction with Approximate Inference

2017 · Neural Information Processing Systems

In this work, we try to understand the differences between exact and approximate inference algorithms in structured prediction. We compare the estimation and approximation error of both underestimate and overestimate models. The result shows that, …

Scaling up Open Tagging from Tens to Thousands: Comprehension Empowered Attribute Value Extraction from Product Title

2019

Supplementing product information by extracting attribute values from title is a crucial task in e-Commerce domain. Previous studies treat each attribute only as an entity type and build one set of NER tags (e.g., BIO) …

Boosting the Speed of Entity Alignment 10 ×: Dual Attention Matching Network with Normalized Hard Sample Mining

2021

Seeking the equivalent entities among multi-source Knowledge Graphs (KGs) is the pivotal step to KGs integration, also known as entity alignment (EA). However, most existing EA methods are inefficient and poor in scalability. A recent …

K-Level Reasoning: Establishing Higher Order Beliefs in Large Language Models for Strategic Reasoning

2024 · arXiv (Cornell University)

Strategic reasoning is a complex yet essential capability for intelligent agents. It requires Large Language Model (LLM) agents to adapt their strategies dynamically in multi-agent environments. Unlike static reasoning tasks, success in these contexts depends …

Graph-based Dependency Parsing with Graph Neural Networks

2019

We investigate the problem of efficiently incorporating high-order features into neural graph-based dependency parsing. Instead of explicitly extracting high-order features from intermediate parse trees, we develop a more powerful dependency tree node representation which captures …