Papers by Zi-Yuan Chen

3 papers
UHop: An Unrestricted-Hop Relation Extraction Framework for Knowledge-Based Question Answering (N19-1)

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Challenge: Existing work restricts search from one entity to another to the maximum number of hops . a knowledge graph is a powerful graph structure that encodes knowledge to save and organize it .
Approach: They propose an unrestricted-hop framework which relaxes the restriction by using a transition-based search framework.
Outcome: The proposed framework performs well with state-of-the-art models and is competitive without exhaustive searches.
A Unified RvNN Framework for End-to-End Chinese Discourse Parsing (C18-2)

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Challenge: Existing work on Chinese discourse parser relies on external packages to extract linguistic features from free text.
Approach: They propose an end-to-end Chinese discourse parser based on recursive neural network to jointly model the subtasks including elementary discourse unit segmentation, tree structure construction, center labeling, and sense labeling.
Outcome: The proposed framework achieves state-of-the-art in the Chinese Discourse Treebank dataset.
CLEVA: Chinese Language Models EVAluation Platform (2023.emnlp-demo)

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Challenge: Large language models (LLMs) have revolutionized natural language processing.
Approach: They propose a Chinese-based platform that assesses Chinese LLMs using a standardized workflow and a unique sampling strategy.
Outcome: CLEVA evaluates Chinese LLMs on a standardized workflow and a competitive leaderboard with minimal coding.

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