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Found 3 papers, 1 papers with code
Strong hallucinations from negation and how to fix them
Despite great performance on many tasks, language models (LMs) still struggle with reasoning, sometimes providing responses that cannot possibly be true because they stem from logical incoherence.
Limits for Learning with Language Models
With the advent of large language models (LLMs), the trend in NLP has been to train LLMs on vast amounts of data to solve diverse language understanding and generation tasks.
Analyzing Semantic Faithfulness of Language Models via Input Intervention on Question Answering
While transformer models achieve high performance on standard question answering tasks, we show that they fail to be semantically faithful once we perform these interventions for a significant number of cases (~50% for deletion intervention, and ~20% drop in accuracy for negation intervention).
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