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cs.LG2023
Knowledge Graphs are not Created Equal: Exploring the Properties and Structure of Real KGs
Nedelina Teneva, Estevam Hruschka
Despite the recent popularity of knowledge graph (KG) related tasks and benchmarks such as KG embeddings, link prediction, entity alignment and evaluation of the reasoning abilitie…
cs.CL2023
Distilling Large Language Models using Skill-Occupation Graph Context for HR-Related Tasks
Pouya Pezeshkpour, Hayate Iso, Thom Lake +2
Numerous HR applications are centered around resumes and job descriptions. While they can benefit from advancements in NLP, particularly large language models, their real-world ado…
cs.CL2023
Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks
Aditi Mishra, Sajjadur Rahman, Hannah Kim +2
Large language models (LLMs) are proficient at generating fluent text with minimal task-specific supervision. Yet, their ability to provide well-grounded rationalizations for knowl…