Papers by Manuel Giollo

2 papers
Detecting and Mitigating Challenges in Zero-Shot Video Summarization with Video LLMs (2025.findings-acl)

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Challenge: Video Large Language Models (VLLMs) exhibit impressive zero-shot capabilities in video analysis, but their performance varies significantly depending on the LLM prompt, the characteristics of the video, and the properties of the training data and LLM architecture.
Approach: They propose to use Chain-of-Thought prompting to inject knowledge extracted by external, lightweight models into video summarization benchmarks to evaluate their performance.
Outcome: The proposed solutions improve summarization performance by injecting knowledge extracted by external, lightweight models.
Privacy Preserving Data Selection for Bias Mitigation in Speech Models (2025.acl-industry)

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Challenge: Existing methods for identifying subgroups raise privacy concerns and gather sensitive information at runtime might be impractical.
Approach: They propose a method to identify and train underperforming subgroups and train a model to predict if an utterance belongs to these subgroup.
Outcome: The proposed method reduces biases and improves performance on intent classification and automatic speech recognition tasks.

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