1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
Rebalancing Token Importance in Language Models with TF-IDF Weighted Cross-Entropy Loss
Zhijian Li, Stefan Larson, Kevin Leach
Large language models are typically trained under uniform token weighting, which allows frequent and low-information tokens to dominate learning and can increase the tendency to me…
Revising RVL-CDIP: Quantifying Errors and Test-Train Overlap
Stefan Larson, Attila Nagy, Sam Desai +8
RVL-CDIP is a popular dataset for benchmarking document classifiers. However, the dataset contains ample amounts of label errors as well as non-trivial amounts of test-train overla…
Document Classification using File Names
Zhijian Li, Stefan Larson, Kevin Leach
Rapid document classification is critical in several time-sensitive applications like digital forensics and large-scale media classification. Traditional approaches that rely on he…
Generating Hard-Negative Out-of-Scope Data with ChatGPT for Intent Classification
Zhijian Li, Stefan Larson, Kevin Leach
Intent classifiers must be able to distinguish when a user's utterance does not belong to any supported intent to avoid producing incorrect and unrelated system responses. Although…