Papers by Elena V. Epure
Modeling the Music Genre Perception across Language-Bound Cultures (2020.emnlp-main)
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| Challenge: | a prevalent approach to culturally study music genres assumes that the same music genre is associated with the items in all cultures. |
| Approach: | They propose to use distributed concept embeddings and ontologies to obtain cross-lingual music genre annotations using language-specific semantic representations. |
| Outcome: | The proposed model can be compared with existing models using domain-dependent cross-lingual corpus. |
Probing Pre-trained Auto-regressive Language Models for Named Entity Typing and Recognition (2022.lrec-1)
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| Challenge: | Existing studies have focused on auto-regressive models for generalization in named entity (NE) typing (NET) and recognition (NER) . however, little has been done in this direction for auto-Regressive LMs despite their popularity and potential to express a wide variety of NLP tasks in the same unified format. |
| Approach: | They propose to probe auto-regressive LMs for NET and NER generalization by resorting to meta-learning to assess the model's memorization of NEs. |
| Outcome: | The proposed model performs well on NET and NER generalization tasks, while relying more on NE than contextual cues in few-shot NER. |
Computational Narrative Understanding for Expressive Text-to-Speech (2026.findings-acl)
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| Challenge: | Recent advances in text-to-speech systems have been driven by large, multi-domain speech corpora. |
| Approach: | They propose a large-scale 5.3K hours of expressive speech drawn from character quotations . they fine-tune a flow-matching model and train from scratch . |
| Outcome: | The proposed model improves expressivity and intelligibility while training from scratch improves expressiveness of an autoregressive model. |
Evaluating LLMs for Quotation Attribution in Literary Texts: A Case Study of LLaMa3 (2025.naacl-short)
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| Challenge: | Large Language Models (LLMs) have shown promising results in literary tasks . however, quotation attribution remains a challenging task and methods that generalize across writing styles are lacking analysis regarding book memorization and annotation contamination. |
| Approach: | They evaluate the ability of Llama-3 to attribute utterances of direct-speech to their speaker in novels by assessing the impact of book memorization and annotation contamination. |
| Outcome: | The proposed model outperforms existing models on a corpus of 28 novels and shows that book memorization and annotation contamination do not explain the performance gain. |
Double Entendre: Robust Audio-Based AI-Generated Lyrics Detection via Multi-View Fusion (2025.findings-acl)
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| Challenge: | Existing methods for detecting AI-generated music are weak and vulnerable to audio perturbations. |
| Approach: | They propose a multimodal late-fusion pipeline that combines automatically transcribed sung lyrics and speech features capturing lyrics related information within the audio. |
| Outcome: | The proposed method outperforms existing detectors while being more robust to audio perturbations. |