Papers by Xiaohan Ding
A Multi-Level Benchmark for Causal Language Understanding in Social Media Discourse (2025.emnlp-main)
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| Challenge: | Existing datasets focus on explicit causality in structured text, providing limited support for detecting implicit causal expressions. |
| Approach: | They propose a dataset of Reddit posts annotated across four causal tasks . they use a binary causal classification, explicit vs. implicit causality, cause–effect span extraction and causal gist generation to bridge causal detection and reasoning over informal discourse. |
| Outcome: | The proposed dataset analyzes 10,120 Reddit posts discussing public health related to the COVID-19 pandemic. |
AlignMMBench: Evaluating Chinese Multimodal Alignment in Large Vision-Language Models (2025.acl-long)
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| Challenge: | Existing benchmarks focus on basic abilities using nonverbal methods, such as yes-no and multiple-choice questions. |
| Approach: | They propose a benchmark that provides more nuanced evaluations of alignment capabilities for large Vision-Language Models (VLMs) they use a rule-calibrated evaluator that exceeds GPT-4's evaluation ability and a “alignment score” to assess the robustness and stability of models across diverse prompts. |
| Outcome: | The proposed benchmark covers 13 tasks across three categories and includes both single-turn and multi-turn dialogue scenarios. |