3 citations · 6 across the 5 of their papers we have counts for
5 papers · 1 filter
Deploying a Retrieval based Response Model for Task Oriented Dialogues
Lahari Poddar, György Szarvas, Cheng Wang +3
Task-oriented dialogue systems in industry settings need to have high conversational capability, be easily adaptable to changing situations and conform to business constraints. Thi…
DialAug: Mixing up Dialogue Contexts in Contrastive Learning for Robust Conversational Modeling
Lahari Poddar, Peiyao Wang, Julia Reinspach
Retrieval-based conversational systems learn to rank response candidates for a given dialogue context by computing the similarity between their vector representations. However, tra…
Attention Guided Dialogue State Tracking with Sparse Supervision
Shuailong Liang, Lahari Poddar, Gyuri Szarvas
Existing approaches to Dialogue State Tracking (DST) rely on turn level dialogue state annotations, which are expensive to acquire in large scale. In call centers, for tasks like m…
A Probabilistic Framework for Learning Domain Specific Hierarchical Word Embeddings
Lahari Poddar, Gyorgy Szarvas, Lea Frermann
The meaning of a word often varies depending on its usage in different domains. The standard word embedding models struggle to represent this variation, as they learn a single glob…
Train One Get One Free: Partially Supervised Neural Network for Bug Report Duplicate Detection and Clustering
Lahari Poddar, Leonardo Neves, William Brendel +3
Tracking user reported bugs requires considerable engineering effort in going through many repetitive reports and assigning them to the correct teams. This paper proposes a neural…