3 citations · 5 across the 5 of their papers we have counts for
5 papers
DRAG: Distilling RAG for SLMs from LLMs to Transfer Knowledge and Mitigate Hallucination via Evidence and Graph-based Distillation
Jennifer Chen, Aidar Myrzakhan, Yaxin Luo +3
Retrieval-Augmented Generation (RAG) methods have proven highly effective for tasks requiring factual consistency and robust knowledge retrieval. However, large-scale RAG systems c…
Improving Instruct Models for Free: A Study on Partial Adaptation
Ozan İrsoy, Pengxiang Cheng, Jennifer L. Chen +3
Instruct models, obtained from various instruction tuning or post-training steps, are commonly deemed superior and more usable than their base counterpart. While the model gains in…
Incorporating Human Explanations for Robust Hate Speech Detection
Jennifer L. Chen, Faisal Ladhak, Daniel Li +1
Given the black-box nature and complexity of large transformer language models (LM), concerns about generalizability and robustness present ethical implications for domains such as…
Knowing When to Ask -- Bridging Large Language Models and Data
Prashanth Radhakrishnan, Jennifer Chen, Bo Xu +5
Large Language Models (LLMs) are prone to generating factually incorrect information when responding to queries that involve numerical and statistical data or other timely facts. I…
Exploring Gender Disparities in Time to Diagnosis
Tony Y. Sun, Oliver J. Bear Don't Walk, Jennifer L. Chen +2
Sex and gender-based healthcare disparities contribute to differences in health outcomes. We focus on time to diagnosis (TTD) by conducting two large-scale, complementary analyses…