Papers by Jian-Tao Huang

2 papers
NumHG: A Dataset for Number-Focused Headline Generation (2024.lrec-main)

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Challenge: a lack of fine-grained annotations for accurate numeral generation in headlines is a major roadblock . a new dataset, the NumHG, provides over 27,000 annotated numeral-rich news articles for detailed investigation .
Approach: They propose a dataset that provides annotated numerals for headline generation . they evaluate five well-performing headline-generation models using human evaluation .
Outcome: The proposed dataset provides annotated numeral-rich news articles for detailed investigation.
The Emperor’s New Reasoning: Format Imitation Overshadows Genuine Mathematical Understanding in SFT (2025.emnlp-main)

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Challenge: Recent advances in large language models (LLMs) have yielded impressive gains on mathematical reasoning benchmarks via supervised fine-tuning (SFT).
Approach: They investigate the mechanisms behind SFT improvements in small-scale large language models by examining four key questions: (1) Are performance gains primarily due to format alignment rather than reasoning? (2) Can high-quality supervision encourage genuine reasoning? (4) Are format alignment gains consistent across model sizes and architectures?
Outcome: The proposed models outperform the proprietary models on OlympiadBench and Omni-Math, but lack the brittleness of the models under perturbations to test their reasoning abilities.

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