Papers by Piero Molino

3 papers
Parallax: Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic Formulae (P19-3)

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Challenge: Embeddings are a fundamental component of many modern machine learning and natural language processing models.
Approach: They propose a tool for visualizing embedding spaces using parametric projections . they demonstrate the power of Parallax and propose % task-oriented approach .
Outcome: The proposed tool is based on two-dimensional projections without interpretable semantics . it enhances interpretability and allows for more fine-grained analysis .
Controllable Text Generation with Focused Variation (2020.findings-emnlp)

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Challenge: Focused-Variation Network (FVN) is a new model to control language generation.
Approach: They propose a model that learns discrete latent spaces for each attribute inside codebooks and uses them to generate fluent text.
Outcome: The proposed model can generate fluent and mostly coherent text on two text generation datasets with annotated content and style, and show state-of-the-art performance as assessed by automatic and human evaluations.
Modeling Multi-Action Policy for Task-Oriented Dialogues (D19-1)

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Challenge: Existing approaches to learn dialogue management only predict one action per turn, limiting expressive power of the conversational agent and introducing unnecessary turns of interactions.
Approach: They propose a model based on a recurrent cell called gated Continue-Act-Slots that overcomes the limitations of existing models and proposes a novel policy model that predicts multiple acts for each turn.
Outcome: The proposed model outperforms existing models on the task of predicting multiple acts for each turn.

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