129 citations · 663 across the 44 of their papers we have counts for
49 papers
Graph Query Generation with Constraint-guided Large Language Agents
Mengying Wang, Nicolaas Jedema, Rahul Pandey +3
Knowledge Graph Question Answering (KGQA) has advanced through structured query generation, yet most efforts target RDF/SPARQL, leaving Cypher and property graphs underexplored, de…
Direct Fact Retrieval from Knowledge Graphs without Entity Linking
Jinheon Baek, Alham Fikri Aji, Jens Lehmann +1
There has been a surge of interest in utilizing Knowledge Graphs (KGs) for various natural language processing/understanding tasks. The conventional mechanism to retrieve facts in…
Retention Is All You Need
Karishma Mohiuddin, Mirza Ariful Alam, Mirza Mohtashim Alam +4
Skilled employees are the most important pillars of an organization. Despite this, most organizations face high attrition and turnover rates. While several machine learning models…
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…
An Answer Verbalization Dataset for Conversational Question Answerings over Knowledge Graphs
Endri Kacupaj, Kuldeep Singh, Maria Maleshkova +1
We introduce a new dataset for conversational question answering over Knowledge Graphs (KGs) with verbalized answers. Question answering over KGs is currently focused on answer gen…
Transformer with Tree-order Encoding for Neural Program Generation
Klaudia-Doris Thellmann, Bernhard Stadler, Ricardo Usbeck +1
While a considerable amount of semantic parsing approaches have employed RNN architectures for code generation tasks, there have been only few attempts to investigate the applicabi…
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…
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…
Time-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphs
Chengjin Xu, Fenglong Su, Jens Lehmann
Entity alignment aims to identify equivalent entity pairs between different knowledge graphs (KGs). Recently, the availability of temporal KGs (TKGs) that contain time information…
LEMON: LanguagE ModeL for Negative Sampling of Knowledge Graph Embeddings
Md Rashad Al Hasan Rony, Mirza Mohtashim Alam, Semab Ali +2
Knowledge Graph Embedding models have become an important area of machine learning.Those models provide a latent representation of entities and relations in a knowledge graph which…
Geometric Algebra based Embeddings for Static and Temporal Knowledge Graph Completion
Chengjin Xu, Mojtaba Nayyeri, Yung-Yu Chen +1
Recent years, Knowledge Graph Embeddings (KGEs) have shown promising performance on link prediction tasks by mapping the entities and relations from a Knowledge Graph (KG) into a g…
Survey on English Entity Linking on Wikidata
Cedric Möller, Jens Lehmann, Ricardo Usbeck
Wikidata is a frequently updated, community-driven, and multilingual knowledge graph. Hence, Wikidata is an attractive basis for Entity Linking, which is evident by the recent incr…
Improving Inductive Link Prediction Using Hyper-Relational Facts
Mehdi Ali, Max Berrendorf, Mikhail Galkin +4
For many years, link prediction on knowledge graphs (KGs) has been a purely transductive task, not allowing for reasoning on unseen entities. Recently, increasing efforts are put i…
Trans4E: Link Prediction on Scholarly Knowledge Graphs
Mojtaba Nayyeri, Gokce Muge Cil, Sahar Vahdati +8
The incompleteness of Knowledge Graphs (KGs) is a crucial issue affecting the quality of AI-based services. In the scholarly domain, KGs describing research publications typically…
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…
Multiple Run Ensemble Learning with Low-Dimensional Knowledge Graph Embeddings
Chengjin Xu, Mojtaba Nayyeri, Sahar Vahdati +1
Among the top approaches of recent years, link prediction using knowledge graph embedding (KGE) models has gained significant attention for knowledge graph completion. Various embe…
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…
GeoWINE: Geolocation based Wiki, Image,News and Event Retrieval
Golsa Tahmasebzadeh, Endri Kacupaj, Eric Müller-Budack +3
In the context of social media, geolocation inference on news or events has become a very important task. In this paper, we present the GeoWINE (Geolocation-based Wiki-Image-News-E…
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…
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…
ParaQA: A Question Answering Dataset with Paraphrase Responses for Single-Turn Conversation
Endri Kacupaj, Barshana Banerjee, Kuldeep Singh +1
This paper presents ParaQA, a question answering (QA) dataset with multiple paraphrased responses for single-turn conversation over knowledge graphs (KG). The dataset was created u…
Context Transformer with Stacked Pointer Networks for Conversational Question Answering over Knowledge Graphs
Joan Plepi, Endri Kacupaj, Kuldeep Singh +2
Neural semantic parsing approaches have been widely used for Question Answering (QA) systems over knowledge graphs. Such methods provide the flexibility to handle QA datasets with…
CHOLAN: A Modular Approach for Neural Entity Linking on Wikipedia and Wikidata
Manoj Prabhakar Kannan Ravi, Kuldeep Singh, Isaiah Onando Mulang' +3
In this paper, we propose CHOLAN, a modular approach to target end-to-end entity linking (EL) over knowledge bases. CHOLAN consists of a pipeline of two transformer-based models in…
SeMantic AnsweR Type prediction task (SMART) at ISWC 2020 Semantic Web Challenge
Nandana Mihindukulasooriya, Mohnish Dubey, Alfio Gliozzo +3
Each year the International Semantic Web Conference accepts a set of Semantic Web Challenges to establish competitions that will advance the state of the art solutions in any given…