Papers by Suvodip Dey
Towards Robust and Semantically Organised Latent Representations for Unsupervised Text Style Transfer (2022.naacl-main)
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| Challenge: | Recent studies show that auto-encoders perform language generation, smooth sentence interpolation, and style transfer over unseen attributes using unlabelled datasets in a zero-shot manner. |
| Approach: | They propose a discrete token-based perturbation approach to map "similar" sentences close by in latent space. |
| Outcome: | The proposed model can generate and perform language generation, style transfer and sentence interpolation tasks on unlabelled datasets in a zero-shot manner. |
Towards Fair Evaluation of Dialogue State Tracking by Flexible Incorporation of Turn-level Performances (2022.acl-short)
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| Challenge: | Dialogue State Tracking (DST) is a task-oriented conversational agent that keeps track of key information exchanged during a conversation. |
| Approach: | They propose a new evaluation metric called Flexible Goal Accuracy to address shortcomings of JGA. |
| Outcome: | The proposed metric improves on existing metrics and improves performance of turn-level and non-cumulative belief state models. |
Know Your Mistakes: Towards Preventing Overreliance on Task-Oriented Conversational AI Through Accountability Modeling (2025.acl-long)
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| Challenge: | Recent LLMs are known to hallucinate, producing responses that seem plausible but are factually incorrect. |
| Approach: | They propose an accountability model for LLM-based task-oriented dialogue agents to address user overreliance via friction turns in cases of model uncertainty and errors associated with dialogue state tracking (DST). |
| Outcome: | The proposed model improves joint goal accuracy (JGA) of DST output by 3% on two established benchmarks. |