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A Bayesian Approach to Harnessing the Power of LLMs in Authorship
  Attribution

A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution

29 October 2024
Zhengmian Hu
Tong Zheng
Heng Huang
    BDL
ArXiv (abs)PDFHTML

Papers citing "A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution"

7 / 7 papers shown
Title
CAVE: Controllable Authorship Verification Explanations
CAVE: Controllable Authorship Verification Explanations
Sahana Ramnath
Kartik Pandey
Elizabeth Boschee
Xiang Ren
120
2
0
24 Jun 2024
Can Large Language Models Identify Authorship?
Can Large Language Models Identify Authorship?
Baixiang Huang
Canyu Chen
Kai Shu
DeLMO
59
17
0
13 Mar 2024
GPT-4 Technical Report
GPT-4 Technical Report
OpenAI OpenAI
OpenAI Josh Achiam
Steven Adler
Sandhini Agarwal
Lama Ahmad
...
Shengjia Zhao
Tianhao Zheng
Juntang Zhuang
William Zhuk
Barret Zoph
LLMAGMLLM
1.5K
14,748
0
15 Mar 2023
Large Language Models Encode Clinical Knowledge
Large Language Models Encode Clinical Knowledge
K. Singhal
Shekoofeh Azizi
T. Tu
S. S. Mahdavi
Jason W. Wei
...
A. Rajkomar
Joelle Barral
Christopher Semturs
Alan Karthikesalingam
Vivek Natarajan
LM&MAELMAI4MH
158
2,362
0
26 Dec 2022
Identifying Biased Subgroups in Ranking and Classification
Identifying Biased Subgroups in Ranking and Classification
Eliana Pastor
Luca de Alfaro
Elena Baralis
CML
41
11
0
17 Aug 2021
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
880
42,463
0
28 May 2020
Distributed Representations of Sentences and Documents
Distributed Representations of Sentences and Documents
Quoc V. Le
Tomas Mikolov
FaML
262
9,250
0
16 May 2014
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