23 citations · 38 across the 9 of their papers we have counts for
4 papers · 1 filter
Self-Consistency of Large Language Models under Ambiguity
Henning Bartsch, Ole Jorgensen, Domenic Rosati +2
Large language models (LLMs) that do not give consistent answers across contexts are problematic when used for tasks with expectations of consistency, e.g., question-answering, exp…
Detecting Edit Failures In Large Language Models: An Improved Specificity Benchmark
Jason Hoelscher-Obermaier, Julia Persson, Esben Kran +2
Recent model editing techniques promise to mitigate the problem of memorizing false or outdated associations during LLM training. However, we show that these techniques can introdu…
Leveraging knowledge graphs to update scientific word embeddings using latent semantic imputation
Jason Hoelscher-Obermaier, Edward Stevinson, Valentin Stauber +4
The most interesting words in scientific texts will often be novel or rare. This presents a challenge for scientific word embedding models to determine quality embedding vectors fo…
Domain-adaptation of spherical embeddings
Mihalis Gongolidis, Jeremy Minton, Ronin Wu +3
Domain adaptation of embedding models, updating a generic embedding to the language of a specific domain, is a proven technique for domains that have insufficient data to train an…