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20122025
most citedEnd-to-End Open-Domain Question Answering with BERTserini

413 citations · 3.1k across the 143 of their papers we have counts for

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46 papers · 1 filter

cs.CL2023

Rank-without-GPT: Building GPT-Independent Listwise Rerankers on Open-Source Large Language Models

Xinyu Zhang, Sebastian Hofstätter, Patrick Lewis +2

Listwise rerankers based on large language models (LLM) are the zero-shot state-of-the-art. However, current works in this direction all depend on the GPT models, making it a singl…

cs.CL2023★ 1 cited

"Knowing When You Don't Know": A Multilingual Relevance Assessment Dataset for Robust Retrieval-Augmented Generation

Nandan Thakur, Luiz Bonifacio, Xinyu Zhang +8

Retrieval-Augmented Generation (RAG) grounds Large Language Model (LLM) output by leveraging external knowledge sources to reduce factual hallucinations. However, prior work lacks…

cs.CL2023

What Do Llamas Really Think? Revealing Preference Biases in Language Model Representations

Raphael Tang, Xinyu Zhang, Jimmy Lin +1

Do large language models (LLMs) exhibit sociodemographic biases, even when they decline to respond? To bypass their refusal to "speak," we study this research question by probing c…

cs.CL2023★ 29 cited

HAGRID: A Human-LLM Collaborative Dataset for Generative Information-Seeking with Attribution

Ehsan Kamalloo, Aref Jafari, Xinyu Zhang +2

The rise of large language models (LLMs) had a transformative impact on search, ushering in a new era of search engines that are capable of generating search results in natural lan…

cs.CL2023

GAIA Search: Hugging Face and Pyserini Interoperability for NLP Training Data Exploration

Aleksandra Piktus, Odunayo Ogundepo, Christopher Akiki +6

Noticing the urgent need to provide tools for fast and user-friendly qualitative analysis of large-scale textual corpora of the modern NLP, we propose to turn to the mature and wel…

cs.CL2023

Regex-augmented Domain Transfer Topic Classification based on a Pre-trained Language Model: An application in Financial Domain

Vanessa Liao, Syed Shariyar Murtaza, Yifan Nie +1

A common way to use large pre-trained language models for downstream tasks is to fine tune them using additional layers. This may not work well if downstream domain is a specialize…