Papers by Lorenzo De Mattei
Invisible to People but not to Machines: Evaluation of Style-aware HeadlineGeneration in Absence of Reliable Human Judgment (2020.lrec-1)
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| Challenge: | Using a data alignment strategy and different training/testing settings, we aim at decoupling content from style and preserving the latter in generation. |
| Approach: | They propose a fine-grained evaluation strategy based on automatic classification to evaluate generated headlines' quality in terms of their newspaper-compliance. |
| Outcome: | The proposed model learns newspaper-specific style, but humans aren't reliable judges for this task, and deserves particular care in its design. |
JuriFindIT: an Italian legal retrieval dataset (2026.findings-eacl)
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| Challenge: | Statutory article retrieval (SAR) targets retrieval of legislative provisions relevant to a natural language question. |
| Approach: | They propose a pipeline that integrates dense encoders with an heterogeneous legislative graph . they propose statutory article retrieval (SAR) is the first SAR dataset for the italian legal domain . |
| Outcome: | The proposed pipeline improves over existing approaches. |
Norm It! Lexical Normalization for Italian and Its Downstream Effects for Dependency Parsing (2020.lrec-1)
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| Challenge: | Existing tools for lexical normalization of social media data are designed with canonical texts in mind, and this makes it difficult to process data in multiple languages. |
| Approach: | They propose to create a lexical normalization dataset for Italian and analyze the inter-annotator agreement for this task. |
| Outcome: | The proposed model improves the parsing of social media data in Italian and shows that it can be used to translate non-standard social media content to canonical language. |
Is this Sentence Difficult? Do you Agree? (D18-1)
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| Challenge: | a crowdsourcing-based approach to model sentence complexity is proposed . word-level predictors shown to correlate with greater processing difficulties are e.g. word frequency, age of acquisition, root frequency effect, orthographic neighbourhood frequency . |
| Approach: | They propose a crowdsourcing-based approach to model human perception of sentence complexity using a corpus of sentences rated with judgments of complexity for two typologically-different languages. |
| Outcome: | The proposed model predicts agreement among annotators independently from the assigned judgment and the perception of sentence complexity in Italian and English. |