5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Learning to Generate Answers with Citations via Factual Consistency Models
Rami Aly, Zhiqiang Tang, Samson Tan +1
Large Language Models (LLMs) frequently hallucinate, impeding their reliability in mission-critical situations. One approach to address this issue is to provide citations to releva…
cs.CL2024★ 5 cited
Lessons from the Trenches on Reproducible Evaluation of Language Models
Stella Biderman, Hailey Schoelkopf, Lintang Sutawika +27
Reliable evaluation of language models (LMs) remains an open challenge. Re- searchers and engineers face methodological issues such as the sensitivity of models to evaluation setup…
cs.CL2024
Extreme Miscalibration and the Illusion of Adversarial Robustness
Vyas Raina, Samson Tan, Volkan Cevher +3
Deep learning-based Natural Language Processing (NLP) models are vulnerable to adversarial attacks, where small perturbations can cause a model to misclassify. Adversarial Training…