Papers by Adriano Veloso

3 papers
Synthetic Data Fine-Tuning for Effective Team Formation in Enterprises (2026.eacl-industry)

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Challenge: Existing algorithms for semantic search fine-tune text embeddings to retrieve and rank documents . word embedders allow search systems to measure semantic similarity between vectors .
Approach: They evaluate the effectiveness of synthetic data fine-tuning for Semantic Search in a real-world Enterprise Team Formation problem scenario.
Outcome: The proposed model outperforms existing models on a human-curated dataset.
Automated Essay Scoring in the Presence of Biased Ratings (N18-1)

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Challenge: Existing studies on rater effects in general settings have not investigated how rater bias affects automated essay scoring.
Approach: They propose to model rater bias by removing essays associated with potentially biased scores from annotated corpus.
Outcome: The proposed model is based on comments provided by raters and is compared with existing corpus.
Computing with Subjectivity Lexicons (2020.lrec-1)

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Challenge: a new set of lexicons for expressing subjectivity in text documents is presented . lexiconics are useful resources for identifying semantics relevant to sentiment, emotion, personality, language bias, mood, and attitude.
Approach: They propose a set of lexicons for expressing subjectivity in Brazilian Portuguese text documents . they use word embedding techniques to capture semantically related words to the ones in the lexicos .
Outcome: The proposed lexicons represent different subjectivity dimensions and are more compact in number of terms.

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