1 citations · 3 across the 10 of their papers we have counts for
10 papers
KGCQual: An Interpretable Framework for Evaluating the Knowledge Graph Construction Quality from Text
Nipun Misra, Vikranth Udandarao, Aanchal Gupta +3
Knowledge Graphs (KGs) are increasingly constructed through automated extraction pipelines; however, such systems often introduce spurious or incomplete triples, which degrade down…
InductWave: Inductive Multi-Hop Logical Query Answering on Knowledge Graphs
Mayank Kharbanda, Michael Cochez, Rajiv Ratn Shah +1
Logical Multi-Hop Query Answering over Knowledge Graphs (KGs) can be formulated as querying, with an implicit completeness assumption. Current works mainly focus on Existential Fir…
Beyond Binary Moral Judgment: Modeling Ethical Pluralism in AI
Aisha Aijaz, Rahul Goel, Arnav Batra +1
Critical decision-making in socially consequential spaces is increasingly involving AI systems at varying capacities. Yet, despite the ubiquity of autonomous systems, most approach…
Expected Moral Shortfall for Ethical Competence in Decision-making Models
Aisha Aijaz, Raghava Mutharaju, Manohar Kumar
Moral cognition is a crucial yet underexplored aspect of decision-making in AI models. Regardless of the application domain, it should be a consideration that allows for ethically…
ApplE: A Modular Ontology of Applied Ethics and Event Context for Ethical Decision Modeling
Aisha Aijaz, Raghava Mutharaju, Manohar Kumar
Applied ethics applies ethical decision-making to domain-specific contexts using contextual information such as agents, actions, temporal and spatial settings, and theoretical cons…
RConE: Rough Cone Embedding for Multi-Hop Logical Query Answering on Multi-Modal Knowledge Graphs
Mayank Kharbanda, Rajiv Ratn Shah, Raghava Mutharaju
Multi-hop query answering over a Knowledge Graph (KG) involves traversing one or more hops from the start node to answer a query. Path-based and logic-based methods are state-of-th…
Knowledge-Driven Cross-Document Relation Extraction
Monika Jain, Raghava Mutharaju, Kuldeep Singh +1
Relation extraction (RE) is a well-known NLP application often treated as a sentence- or document-level task. However, a handful of recent efforts explore it across documents or in…
Revisiting Document-Level Relation Extraction with Context-Guided Link Prediction
Monika Jain, Raghava Mutharaju, Ramakanth Kavuluru +1
Document-level relation extraction (DocRE) poses the challenge of identifying relationships between entities within a document as opposed to the traditional RE setting where a sing…
SERC: Syntactic and Semantic Sequence based Event Relation Classification
Kritika Venkatachalam, Raghava Mutharaju, Sumit Bhatia
Temporal and causal relations play an important role in determining the dependencies between events. Classifying the temporal and causal relations between events has many applicati…
Why Settle for Just One? Extending EL++ Ontology Embeddings with Many-to-Many Relationships
Biswesh Mohapatra, Sumit Bhatia, Raghava Mutharaju +1
Knowledge Graph (KG) embeddings provide a low-dimensional representation of entities and relations of a Knowledge Graph and are used successfully for various applications such as q…