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Found 3 papers, 3 papers with code
What Evidence Do Language Models Find Convincing?
Retrieval-augmented language models are being increasingly tasked with subjective, contentious, and conflicting queries such as "is aspartame linked to cancer".
Poisoning Language Models During Instruction Tuning
In this work, we show that adversaries can contribute poison examples to these datasets, allowing them to manipulate model predictions whenever a desired trigger phrase appears in the input.
GLUECons: A Generic Benchmark for Learning Under Constraints
Recent research has shown that integrating domain knowledge into deep learning architectures is effective -- it helps reduce the amount of required data, improves the accuracy of the models' decisions, and improves the interpretability of models.
