4 papers
ColBERT-Att: Late-Interaction Meets Attention for Enhanced Retrieval
Raj Nath Patel, Sourav Dutta
Vector embeddings from pre-trained language models form a core component in Neural Information Retrieval systems across a multitude of knowledge extraction tasks. The paradigm of l…
DROID: Dual Representation for Out-of-Scope Intent Detection
Wael Rashwan, Hossam M. Zawbaa, Sourav Dutta +1
Detecting out-of-scope (OOS) user utterances remains a key challenge in task-oriented dialogue systems and, more broadly, in open-set intent recognition. Existing approaches often…
Improved Out-of-Scope Intent Classification with Dual Encoding and Threshold-based Re-Classification
Hossam M. Zawbaa, Wael Rashwan, Sourav Dutta +1
Detecting out-of-scope user utterances is essential for task-oriented dialogues and intent classification. Current methodologies face difficulties with the unpredictable distributi…
AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification
Yongxin Huang, Kexin Wang, Sourav Dutta +3
Recent work has found that few-shot sentence classification based on pre-trained Sentence Encoders (SEs) is efficient, robust, and effective. In this work, we investigate strategie…