27 citations · 33 across the 9 of their papers we have counts for
6 papers · 1 filter
Adaptive Multi-Agent Response Refinement in Conversational Systems
Soyeong Jeong, Aparna Elangovan, Emine Yilmaz +1
Large Language Models (LLMs) have demonstrated remarkable success in conversational systems by generating human-like responses. However, they can fall short, especially when requir…
Salient Information Prompting to Steer Content in Prompt-based Abstractive Summarization
Lei Xu, Mohammed Asad Karim, Saket Dingliwal +1
Large language models (LLMs) can generate fluent summaries across domains using prompting techniques, reducing the need to train models for summarization applications. However, cra…
ConSiDERS-The-Human Evaluation Framework: Rethinking Human Evaluation for Generative Large Language Models
Aparna Elangovan, Ling Liu, Lei Xu +2
In this position paper, we argue that human evaluation of generative large language models (LLMs) should be a multidisciplinary undertaking that draws upon insights from discipline…
Principles from Clinical Research for NLP Model Generalization
Aparna Elangovan, Jiayuan He, Yuan Li +1
The NLP community typically relies on performance of a model on a held-out test set to assess generalization. Performance drops observed in datasets outside of official test sets a…
Memorization vs. Generalization: Quantifying Data Leakage in NLP Performance Evaluation
Aparna Elangovan, Jiayuan He, Karin Verspoor
Public datasets are often used to evaluate the efficacy and generalizability of state-of-the-art methods for many tasks in natural language processing (NLP). However, the presence…
Assigning function to protein-protein interactions: a weakly supervised BioBERT based approach using PubMed abstracts
Aparna Elangovan, Melissa Davis, Karin Verspoor
Motivation: Protein-protein interactions (PPI) are critical to the function of proteins in both normal and diseased cells, and many critical protein functions are mediated by inter…