49 citations · 201 across the 21 of their papers we have counts for
5 papers · 1 filter
Beemo: Benchmark of Expert-edited Machine-generated Outputs
Ekaterina Artemova, Jason Lucas, Saranya Venkatraman +4
The rapid proliferation of large language models (LLMs) has increased the volume of machine-generated texts (MGTs) and blurred text authorship in various domains. However, most exi…
LLM-DetectAIve: a Tool for Fine-Grained Machine-Generated Text Detection
Mervat Abassy, Kareem Elozeiri, Alexander Aziz +21
The ease of access to large language models (LLMs) has enabled a widespread of machine-generated texts, and now it is often hard to tell whether a piece of text was human-written o…
Papilusion at DAGPap24: Paper or Illusion? Detecting AI-generated Scientific Papers
Nikita Andreev, Alexander Shirnin, Vladislav Mikhailov +1
This paper presents Papilusion, an AI-generated scientific text detector developed within the DAGPap24 shared task on detecting automatically generated scientific papers. We propos…
AIpom at SemEval-2024 Task 8: Detecting AI-produced Outputs in M4
Alexander Shirnin, Nikita Andreev, Vladislav Mikhailov +1
This paper describes AIpom, a system designed to detect a boundary between human-written and machine-generated text (SemEval-2024 Task 8, Subtask C: Human-Machine Mixed Text Detect…
LUNA: A Framework for Language Understanding and Naturalness Assessment
Marat Saidov, Aleksandra Bakalova, Ekaterina Taktasheva +2
The evaluation of Natural Language Generation (NLG) models has gained increased attention, urging the development of metrics that evaluate various aspects of generated text. LUNA a…