Papers by Kenan Jiang

2 papers
ComCLIP: Training-Free Compositional Image and Text Matching (2024.naacl-long)

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Challenge: erroneous semantics of individual entities are essentially confounders that cause the matching failure.
Approach: They propose a training-free compositional CLIP model which disentangles input images into subjects, objects, and action subimages and composes CLIP’s vision encoder and text encoder to perform evolving matching over compositional text embedding and subimage embeddments.
Outcome: The proposed model mitigates spurious correlations introduced by the pretrained CLIP models and dynamically evaluates the importance of each component.
Causally Modeling the Linguistic and Social Factors that Predict Email Response (2025.naacl-long)

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Challenge: a key intent behind many emails is to get a reply from the recipient.
Approach: They propose to model the intents, expectations, and responsiveness in email exchanges by using a dataset containing 1800 emails annotated with nuanced types of intents and expectations.
Outcome: The proposed model is based on 1800 emails annotated with nuanced types of intents and expectations . it shows that social status, argumentation, and strength of social connection influence email response rates .

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