Papers by Shuqian Sheng

4 papers
Is Reference Necessary in the Evaluation of NLG Systems? When and Where? (2024.naacl-long)

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Challenge: Despite recent advances in reference-free metrics, it has not been well understood when and where they can be used as an alternative to reference-based metrics.
Approach: They propose to use reference-free metrics to evaluate NLG systems . they find they have a higher correlation with human judgment and greater sensitivity to deficiencies in language quality .
Outcome: The proposed metrics exhibit higher correlation with human judgment and greater sensitivity to deficiencies in language quality.
RepEval: Effective Text Evaluation with LLM Representation (2024.emnlp-main)

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Challenge: Traditional metrics for automatic text evaluation are tailored to specific tasks, while LLM-based evaluation metrics are costly.
Approach: They propose a metric that leverages projections of LLM representations for evaluation.
Outcome: The proposed metric exhibits higher correlation with human judgments than previous methods on 14 datasets.
Unsupervised Graph-Text Mutual Conversion with a Unified Pretrained Language Model (2023.acl-long)

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Challenge: Existing unsupervised approaches for learning knowledge graphs require multiple modules and require entity information or relation type for training.
Approach: They propose a method that uses a unified pretrained language model to achieve fully unsupervised graph-text mutual conversion for the first time.
Outcome: The proposed method outperforms state-of-the-art methods for G2T and T2G tasks by fine-tuning only one pretrained model.
Exploring and Verbalizing Academic Ideas by Concept Co-occurrence (2023.acl-long)

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Challenge: a new framework for academic idea inspiration is being developed for academic research assistants . number of academic publications is increasing exponentially, making it difficult for an independent researcher to understand these papers thoroughly.
Approach: They propose a framework based on concept co-occurrence for academic idea inspiration . they construct evolving concept graphs according to the co-existence relationship of concepts from 20 disciplines or topics .
Outcome: The proposed system can be used to explore connections between academic concepts and verbalize the new ideas.

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