Papers by Razvan Bunescu
A Text-Based Recommender System that Leverages Explicit Affective State Preferences (2025.emnlp-main)
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| Challenge: | Existing systems that leverage user preferences that are implicit in user-item rating histories can be slow to track changes in user preferences and imprecise for users with diverse preferences. |
| Approach: | They propose a novel recommendation task that leverages a wide range of affective states sought explicitly by the user to identify items that induce those affective state. |
| Outcome: | The proposed model can leverage a wide range of affective states sought explicitly by the user to identify items likely to induce those affective state. |
Context Dependent Semantic Parsing over Temporally Structured Data (N19-1)
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| Challenge: | Existing semantic parsing tools only allow for natural language interactions, but the graphical interface could be improved significantly. |
| Approach: | They propose a semantic parsing setting that allows users to query the system using both natural language questions and actions within a graphical user interface. |
| Outcome: | The proposed architecture outperforms standard sequence generation baselines and achieves sequence-level accuracy of 88.7% on artificial data and 74.8% on real data. |
McMining: Automated Discovery of Misconceptions in Student Code (2026.eacl-short)
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| Challenge: | misconceptions can lead to bugs and slow down learning of related concepts . a misconception is a belief in a false statement, such as believing that the earth is flat or that real numbers are countable. |
| Approach: | They propose a task of mining programming misconceptions from student code samples . they introduce McMining, which uses a benchmark dataset to identify misconceptions . |
| Outcome: | The proposed models are effective at finding misconceptions in student code. |