Nelson F. Liu

Stronger Baselines for Retrieval-Augmented Generation with Long-Context Language Models

2025 · arXiv (Cornell University)

With the rise of long-context language models (LMs) capable of processing tens of thousands of tokens in a single context window, do multi-stage retrieval-augmented generation (RAG) pipelines still offer measurable benefits over simpler, single-stage approaches? …

Linguistic Knowledge and Transferability of Contextual Representations

2019

Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, Noah A. Smith. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long …

Barack’s Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling

2019

Modeling human language requires the ability to not only generate fluent text but also encode factual knowledge. However, traditional language models are only capable of remembering facts seen at training time, and often have difficulty …

Lost in the Middle: How Language Models Use Long Contexts

2024 · Transactions of the Association for Computational Linguistics

Abstract While recent language models have the ability to take long contexts as input, relatively little is known about how well they use longer context. We analyze the performance of language models on two tasks …