Papers by Xingcheng Yao

2 papers
V-ALPHASOCIAL: Benchmark and Self-Reflective Chain-of-Thought Generation for Visual Social Commonsense Reasoning (2025.findings-acl)

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Challenge: Social commonsense reasoning is a multimodal task that requires both textual and visual cues.
Approach: They propose a method that integrates visual cues into social commonsense reasoning tasks.
Outcome: The proposed method improves social commonsense reasoning on a multimodal foundation model.
SimCSE: Simple Contrastive Learning of Sentence Embeddings (2021.emnlp-main)

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Challenge: Existing methods for learning universal sentence embeddings are based on unsupervised approaches with only dropout as noise.
Approach: They propose an unsupervised approach that takes an input sentence and predicts itself in a contrastive objective with only standard dropout used as noise.
Outcome: The proposed framework performs on par with previous supervised approaches and can produce superior sentence embeddings from unlabeled or labeled data.

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