6 papers
Tree-of-Concerns: Hierarchical Multi-Agent Debate for Unstated-Limitation Extraction in Scientific Critique
Sahil Mishra, Niranjan Rajeev, Tanmoy Chakraborty
As scientific literature grows and papers increasingly under-report limitations, multi-agent LLMs offer a promising approach to systematically uncover these hidden failure modes. H…
Polaris: Coupled Orbital Polar Embeddings for Hierarchical Concept Learning
Sahil Mishra, Srinitish Srinivasan, Sourish Dasgupta +1
Real-world knowledge is often organized as hierarchies such as product taxonomies, medical ontologies, and label trees, yet learning hierarchical representations is challenging due…
TaxoBell: Gaussian Box Embeddings for Self-Supervised Taxonomy Expansion
Sahil Mishra, Srinitish Srinivasan, Srikanta Bedathur +1
Taxonomies form the backbone of structured knowledge representation across diverse domains, enabling applications such as e-commerce and semantic search. Yet, manual taxonomy expan…
Rank, Chunk and Expand: Lineage-Oriented Reasoning for Taxonomy Expansion
Sahil Mishra, Kumar Arjun, Tanmoy Chakraborty
Taxonomies are hierarchical knowledge graphs crucial for recommendation systems, and web applications. As data grows, expanding taxonomies is essential, but existing methods face k…
QuanTaxo: A Quantum Approach to Self-Supervised Taxonomy Expansion
Sahil Mishra, Avi Patni, Niladri Chatterjee +1
A taxonomy is a hierarchical graph containing knowledge to provide valuable insights for various web applications. However, the manual construction of taxonomies requires significa…
FLAME: Self-Supervised Low-Resource Taxonomy Expansion using Large Language Models
Sahil Mishra, Ujjwal Sudev, Tanmoy Chakraborty
Taxonomies represent an arborescence hierarchical structure that establishes relationships among entities to convey knowledge within a specific domain. Each edge in the taxonomy si…