9 citations · 24 across the 27 of their papers we have counts for
8 papers · 1 filter
DoGMaTiQ: Automated Generation of Question-and-Answer Nuggets for Report Evaluation
Bryan Li, William Walden, Yu Hou +6
Evaluation of long-form, citation-backed reports has lately received significant attention due to the wide-scale adoption of retrieval-augmented generation (RAG) systems. Core to m…
FACTUM: Mechanistic Detection of Citation Hallucination in Long-Form RAG
Maxime Dassen, Rebecca Kotula, Kenton Murray +5
Retrieval-Augmented Generation (RAG) models are critically undermined by citation hallucinations, a deceptive failure where a model cites a source that fails to support its claim.…
Principled Context Engineering for RAG: Statistical Guarantees via Conformal Prediction
Debashish Chakraborty, Eugene Yang, Daniel Khashabi +2
Retrieval-Augmented Generation (RAG) enhances factual grounding in large language models (LLMs) by incorporating retrieved evidence, but LLM accuracy declines when long or noisy co…
mmBERT: A Modern Multilingual Encoder with Annealed Language Learning
Marc Marone, Orion Weller, William Fleshman +3
Encoder-only languages models are frequently used for a variety of standard machine learning tasks, including classification and retrieval. However, there has been a lack of recent…
Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAG
Dayeon Ki, Marine Carpuat, Paul McNamee +4
Multilingual Retrieval-Augmented Generation (mRAG) systems enable language models to answer knowledge-intensive queries with citation-supported responses across languages. Despite…
Seq vs Seq: An Open Suite of Paired Encoders and Decoders
Orion Weller, Kathryn Ricci, Marc Marone +3
The large language model (LLM) community focuses almost exclusively on decoder-only language models, since they are easier to use for text generation. However, a large subset of th…
CLERC: A Dataset for Legal Case Retrieval and Retrieval-Augmented Analysis Generation
Abe Bohan Hou, Orion Weller, Guanghui Qin +5
Legal professionals need to write analyses that rely on citations to relevant precedents, i.e., previous case decisions. Intelligent systems assisting legal professionals in writin…
Dated Data: Tracing Knowledge Cutoffs in Large Language Models
Jeffrey Cheng, Marc Marone, Orion Weller +3
Released Large Language Models (LLMs) are often paired with a claimed knowledge cutoff date, or the dates at which training data was gathered. Such information is crucial for appli…