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Found 4 papers, 4 papers with code
Generating Benchmarks for Factuality Evaluation of Language Models
FACTOR automatically transforms a factual corpus of interest into a benchmark evaluating an LM's propensity to generate true facts from the corpus vs. similar but incorrect statements.
Parallel Context Windows for Large Language Models
We present Parallel Context Windows (PCW), a method that alleviates the context window restriction for any off-the-shelf LLM without further training.
Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias
We find that while larger models outperform smaller ones, the probability that their mistakes are caused by gender bias is higher.
Data Contamination: From Memorization to Exploitation
Experiments with two models and three downstream tasks show that exploitation exists in some cases, but in others the models memorize the contaminated data, but do not exploit it.
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