Papers by Kunyu Jiang

2 papers
MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation (2025.emnlp-main)

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Challenge: Existing large language model evaluation benchmarks focus on English, while current multilingual tasks lack parallel questions that specifically assess cross-lingual reasoning abilities.
Approach: They propose a comprehensive benchmark covering 29 languages, built on an English benchmark.
Outcome: The MMLU-ProX is a comprehensive benchmark covering 29 languages, built on an English benchmark.
Digest the Knowledge: Large Language Models empowered Message Passing for Knowledge Graph Question Answering (2025.acl-long)

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Challenge: Existing methods to augment large language models (LLMs) with external knowledge are unorganized and unorganized.
Approach: They propose a method that learns a concise facts graph and encodes it into multi-level lists of texts to augment LLMs.
Outcome: The proposed method improves on all 5 knowledge graph question answering datasets and offers human-level semantic explainability.

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