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Found 3 papers, 1 papers with code
PAT-Questions: A Self-Updating Benchmark for Present-Anchored Temporal Question-Answering
Existing work on Temporal Question Answering (TQA) has predominantly focused on questions anchored to specific timestamps or events (e. g. "Who was the US president in 1970?").
EcoRank: Budget-Constrained Text Re-ranking Using Large Language Models
We study how to maximize the re-ranking performance given a budget, by navigating the vast search spaces of prompt choices, LLM APIs, and budget splits.
NORMY: Non-Uniform History Modeling for Open Retrieval Conversational Question Answering
A typical OrConvQA pipeline consists of three modules: a Retriever to retrieve relevant documents from the collection, a Reranker to rerank them given the question and the context, and a Reader to extract an answer span.
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