2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.IR2026
Revisiting RAG Retrievers: An Information Theoretic Benchmark
Wenqing Zheng, Dmitri Kalaev, Noah Fatsi +5
Retrieval-Augmented Generation (RAG) systems rely critically on the retriever module to surface relevant context for large language models. Although numerous retrievers have recent…
cs.IR2025
Tuning-Free LLM Can Build A Strong Recommender Under Sparse Connectivity And Knowledge Gap Via Extracting Intent
Wenqing Zheng, Noah Fatsi, Daniel Barcklow +5
Recent advances in recommendation with large language models (LLMs) often rely on either commonsense augmentation at the item-category level or implicit intent modeling on existing…
cs.LG2023★ 2 cited
The Disagreement Problem in Faithfulness Metrics
Brian Barr, Noah Fatsi, Leif Hancox-Li +3
The field of explainable artificial intelligence (XAI) aims to explain how black-box machine learning models work. Much of the work centers around the holy grail of providing post-…