Papers by Paola Cascante-Bonilla

3 papers
Chat-crowd: A Dialog-based Platform for Visual Layout Composition (N19-4)

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Challenge: We present Chat-crowd, an interactive environment for visual layout composition via conversational interactions . system can be integrated with crowdsourcing platforms for both synchronous and asynchronous data collection .
Approach: They introduce an interactive environment for visual layout composition via conversational interactions that supports multiple agents with two conversational roles.
Outcome: The proposed system can be integrated with crowdsourcing platforms for both synchronous and asynchronous data collection and has quality controls on the performance of both types of agents.
Can Hallucination Correction Improve Video-Language Alignment? (2025.findings-acl)

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Challenge: Existing work on hallucination correction for large vision-language models focuses on mitigating hallucisations, but a new approach is needed to improve video-language alignment.
Approach: They propose a self-training framework learning to correct hallucinations in descriptions that do not align with the video content.
Outcome: The proposed framework improves video-language alignment by identifying and correcting inconsistencies in descriptions that do not align with the video content.
PropTest: Automatic Property Testing for Improved Visual Programming (2024.findings-emnlp)

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Challenge: Visual Programming is an alternative to end-to-end black-box visual reasoning models.
Approach: They propose a visual programming strategy that leverages Large Language Models to generate the logic of a program in the form of its source code.
Outcome: The proposed method improves ViperGPT on visual question answering and referring expression comprehension with an LLM.

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