3 papers
cs.CL2026
Dynamically Acquiring Text Content to Enable the Classification of Lesser-known Entities for Real-world Tasks
Fahmida Alam, Ellen Riloff
Existing Natural Language Processing (NLP) resources often lack the task-specific information required for real-world problems and provide limited coverage of lesser-known or newly…
cs.CL2026
Bridging the Long-Tail Gap: Robust Retrieval-Augmented Relation Completion via Multi-Stage Paraphrase Infusion
Fahmida Alam, Mihai Surdeanu, Ellen Riloff
Large language models (LLMs) struggle with relation completion (RC), both with and without retrieval-augmented generation (RAG), particularly when the required information is rare…
cs.CL2025
Say Less, Mean More: Leveraging Pragmatics in Retrieval-Augmented Generation
Haris Riaz, Ellen Riloff, Mihai Surdeanu
We propose a simple, unsupervised method that injects pragmatic principles in retrieval-augmented generation (RAG) frameworks such as Dense Passage Retrieval to enhance the utility…