6 papers
Beyond Memorization: Distinguishing Between Pattern-Based and Epistemic Reasoning in LLMs Using Epistemic Puzzles
Adi Gabay, Gabriel Stanovsky, Liat Peterfreund
Epistemic reasoning requires agents to infer the state of the world from partial observations and information about other agents' knowledge. Prior work evaluating LLMs on epistemic…
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'…
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…
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…
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…