4 papers
How Important is `Perfect' English for Machine Translation Prompts?
Patrícia Schmidtová, Niyati Bafna, Seth Aycock +4
Large language models (LLMs) have achieved top results in recent machine translation evaluations, but they are also known to be sensitive to errors and perturbations in their promp…
LLM-as-a-qualitative-judge: automating error analysis in natural language generation
Nadezhda Chirkova, Tunde Oluwaseyi Ajayi, Seth Aycock +4
Prompting large language models (LLMs) to evaluate generated text, known as LLM-as-a-judge, has become a standard evaluation approach in natural language generation (NLG), but is p…
Please Translate Again: Two Simple Experiments on Whether Human-Like Reasoning Helps Translation
Di Wu, Seth Aycock, Christof Monz
Large Language Models (LLMs) demonstrate strong reasoning capabilities for many tasks, often by explicitly decomposing the task via Chain-of-Thought (CoT) reasoning. Recent work on…
Masks and Mimicry: Strategic Obfuscation and Impersonation Attacks on Authorship Verification
Kenneth Alperin, Rohan Leekha, Adaku Uchendu +5
The increasing use of Artificial Intelligence (AI) technologies, such as Large Language Models (LLMs) has led to nontrivial improvements in various tasks, including accurate author…