Papers by Zonghai Hu

2 papers
F2TEval: Human-Aligned Multi-Dimensional Evaluation for Figure-to-Text Task (2025.emnlp-main)

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Challenge: Existing evaluation methods for Figure-to-Text tasks are limited due to the inherent ambiguity and semantic compression of figures, the generated texts suffer from factual inaccuracies, incomplete coverage, and weak logical reasoning.
Approach: They propose a five-dimensional reference-free evaluation method aligned with expert criteria to support fine-grained evaluation.
Outcome: The proposed method outperforms Gemini-2.0 and Claude-3.5 with only 0.9B parameters.
SarcNet: A Multilingual Multimodal Sarcasm Detection Dataset (2024.lrec-main)

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Challenge: Sarcasm is an implicit form of sarcasm, involving an intended meaning that contradicts the literal expression . human use conflict between factual information and a statement as cues to detect sarcasm . sarkasmatic analysis is challenging due to its implicit nature .
Approach: They propose a multimodal sarcasm detection dataset that uses multiple modalities to detect sarcasm.
Outcome: The proposed model improves on previous models based on a single label . human sarcasm cannot be detected using a unified label across multiple modalities .

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