Papers by Kalpa Gunaratna
IMRNNs: An Efficient Method for Interpretable Dense Retrieval via Embedding Modulation (2026.findings-eacl)
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| Challenge: | Existing dense retrieval methods rely on static embeddings that obscure bidirectional relationship between queries and documents. |
| Approach: | They propose a framework that augments any black-box dense retrievers with dynamic, bidirectional modulation at inference time. |
| Outcome: | a new framework augments any dense retriever with dynamic, bidirectional modulation at inference time. |
Explainable Slot Type Attentions to Improve Joint Intent Detection and Slot Filling (2022.findings-emnlp)
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| Challenge: | Existing methods analyze and compute features collectively for all slot types, and have no way to explain slot filling model decisions. |
| Approach: | They propose a method that learns to generate additional slot type specific features to improve accuracy and provides explanations for slot filling decisions for the first time in a joint NLU model. |
| Outcome: | The proposed model improves on two widely used datasets and provides an explanation for slot filling decisions for the first time. |
Switching Heads and Softening Tokens: Turnkey Solutions to Visually Grounded Document QA (2026.findings-acl)
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| Challenge: | Document Question Answering lacks robust, end-to-end solutions capable of handling complex, multi-answer queries without reliance on ad-hoc processing. |
| Approach: | They propose a single-head architecture where coordinates are represented as special tokens within the unified vocabulary. |
| Outcome: | The proposed architectures improve visual grounding but lack spatial precision bound by discretization. |