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20182026
most citedPyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings

89 citations · 289 across the 20 of their papers we have counts for

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16 papers · 1 filter

cs.CL20221 cited

Contrastive Representation Learning for Conversational Question Answering over Knowledge Graphs

Endri Kacupaj, Kuldeep Singh, Maria Maleshkova +1

This paper addresses the task of conversational question answering (ConvQA) over knowledge graphs (KGs). The majority of existing ConvQA methods rely on full supervision signals wi…

cs.CL20221 cited

DialoKG: Knowledge-Structure Aware Task-Oriented Dialogue Generation

Md Rashad Al Hasan Rony, Ricardo Usbeck, Jens Lehmann

Task-oriented dialogue generation is challenging since the underlying knowledge is often dynamic and effectively incorporating knowledge into the learning process is hard. It is pa…

cs.CL20221 cited

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…

cs.CL2021

VOGUE: Answer Verbalization through Multi-Task Learning

Endri Kacupaj, Shyamnath Premnadh, Kuldeep Singh +2

In recent years, there have been significant developments in Question Answering over Knowledge Graphs (KGQA). Despite all the notable advancements, current KGQA systems only focus…

cs.CL20211 cited

VANiLLa : Verbalized Answers in Natural Language at Large Scale

Debanjali Biswas, Mohnish Dubey, Md Rashad Al Hasan Rony +1

In the last years, there have been significant developments in the area of Question Answering over Knowledge Graphs (KGQA). Despite all the notable advancements, current KGQA datas…

cs.CL2021

Conversational Question Answering over Knowledge Graphs with Transformer and Graph Attention Networks

Endri Kacupaj, Joan Plepi, Kuldeep Singh +3

This paper addresses the task of (complex) conversational question answering over a knowledge graph. For this task, we propose LASAGNE (muLti-task semAntic parSing with trAnsformer…