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20232026
most citedScaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models

4 citations · 6 across the 9 of their papers we have counts for

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Showing 2024Show all

2 papers · 1 filter

cs.CL2024

FaithBench: A Diverse Hallucination Benchmark for Summarization by Modern LLMs

Forrest Sheng Bao, Miaoran Li, Renyi Qu +13

Summarization is one of the most common tasks performed by large language models (LLMs), especially in applications like Retrieval-Augmented Generation (RAG). However, existing eva…

cs.IR2024

Can't Hide Behind the API: Stealing Black-Box Commercial Embedding Models

Manveer Singh Tamber, Jasper Xian, Jimmy Lin

Embedding models that generate dense vector representations of text are widely used and hold significant commercial value. Companies such as OpenAI and Cohere offer proprietary emb…