4 papers
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…
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…
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…
Memorization in In-Context Learning
Shahriar Golchin, Mihai Surdeanu, Steven Bethard +2
In-context learning (ICL) has proven to be an effective strategy for improving the performance of large language models (LLMs) with no additional training. However, the exact mecha…