68 citations · 87 across the 7 of their papers we have counts for
9 papers
RoMe: A Robust Metric for Evaluating Natural Language Generation
Md Rashad Al Hasan Rony, Liubov Kovriguina, Debanjan Chaudhuri +2
Evaluating Natural Language Generation (NLG) systems is a challenging task. Firstly, the metric should ensure that the generated hypothesis reflects the reference's semantics. Seco…
Grounding Dialogue Systems via Knowledge Graph Aware Decoding with Pre-trained Transformers
Debanjan Chaudhuri, Md Rashad Al Hasan Rony, Jens Lehmann
Generating knowledge grounded responses in both goal and non-goal oriented dialogue systems is an important research challenge. Knowledge Graphs (KG) can be viewed as an abstractio…
PNEL: Pointer Network based End-To-End Entity Linking over Knowledge Graphs
Debayan Banerjee, Debanjan Chaudhuri, Mohnish Dubey +1
Question Answering systems are generally modelled as a pipeline consisting of a sequence of steps. In such a pipeline, Entity Linking (EL) is often the first step. Several EL model…
End-to-End Entity Linking and Disambiguation leveraging Word and Knowledge Graph Embeddings
Rostislav Nedelchev, Debanjan Chaudhuri, Jens Lehmann +1
Entity linking - connecting entity mentions in a natural language utterance to knowledge graph (KG) entities is a crucial step for question answering over KGs. It is often based on…
Incorporating Joint Embeddings into Goal-Oriented Dialogues with Multi-Task Learning
Firas Kassawat, Debanjan Chaudhuri, Jens Lehmann
Attention-based encoder-decoder neural network models have recently shown promising results in goal-oriented dialogue systems. However, these models struggle to reason over and inc…
Using a KG-Copy Network for Non-Goal Oriented Dialogues
Debanjan Chaudhuri, Md Rashad Al Hasan Rony, Simon Jordan +1
Non-goal oriented, generative dialogue systems lack the ability to generate answers with grounded facts. A knowledge graph can be considered an abstraction of the real world consis…
Improving Response Selection in Multi-Turn Dialogue Systems by Incorporating Domain Knowledge
Debanjan Chaudhuri, Agustinus Kristiadi, Jens Lehmann +1
Building systems that can communicate with humans is a core problem in Artificial Intelligence. This work proposes a novel neural network architecture for response selection in an…
A Retrospective Analysis of the Fake News Challenge Stance Detection Task
Andreas Hanselowski, Avinesh PVS, Benjamin Schiller +4
The 2017 Fake News Challenge Stage 1 (FNC-1) shared task addressed a stance classification task as a crucial first step towards detecting fake news. To date, there is no in-depth a…
EARL: Joint Entity and Relation Linking for Question Answering over Knowledge Graphs
Mohnish Dubey, Debayan Banerjee, Debanjan Chaudhuri +1
Many question answering systems over knowledge graphs rely on entity and relation linking components in order to connect the natural language input to the underlying knowledge grap…