5 papers
Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages
Noam Dahan, Omer Kidron, Gabriel Stanovsky
High quality summarization data remains scarce in under-represented languages. However, historical newspapers, made available through recent digitization efforts, offer an abundant…
HACK: Hallucinations Along Certainty and Knowledge Axes
Adi Simhi, Jonathan Herzig, Itay Itzhak +7
Hallucinations in LLMs present a critical barrier to their reliable usage. Existing research usually categorizes hallucination by their external properties rather than by the LLMs'…
Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs
Itay Itzhak, Yonatan Belinkov, Gabriel Stanovsky
Large language models (LLMs) exhibit cognitive biases -- systematic tendencies of irrational decision-making, similar to those seen in humans. Prior work has found that these biase…
Trust Me, I'm Wrong: LLMs Hallucinate with Certainty Despite Knowing the Answer
Adi Simhi, Itay Itzhak, Fazl Barez +2
Prior work on large language model (LLM) hallucinations has associated them with model uncertainty or inaccurate knowledge. In this work, we define and investigate a distinct type…
The State and Fate of Summarization Datasets: A Survey
Noam Dahan, Gabriel Stanovsky
Automatic summarization has consistently attracted attention due to its versatility and wide application in various downstream tasks. Despite its popularity, we find that annotatio…