2 citations · 3 across the 5 of their papers we have counts for
4 papers · 1 filter
Brittlebench: Quantifying LLM robustness via prompt sensitivity
Angelika Romanou, Mark Ibrahim, Candace Ross +8
Existing evaluation methods largely rely on clean, static benchmarks, which can overestimate true model performance by failing to capture the noise and variability inherent in real…
What's in Common? Multimodal Models Hallucinate When Reasoning Across Scenes
Candace Ross, Florian Bordes, Adina Williams +2
Multimodal language models possess a remarkable ability to handle an open-vocabulary's worth of objects. Yet the best models still suffer from hallucinations when reasoning about s…
Transformers Can Navigate Mazes With Multi-Step Prediction
Niklas Nolte, Ouail Kitouni, Adina Williams +2
Despite their remarkable success in language modeling, transformers trained to predict the next token in a sequence struggle with long-term planning. This limitation is particularl…
The Factorization Curse: Which Tokens You Predict Underlie the Reversal Curse and More
Ouail Kitouni, Niklas Nolte, Diane Bouchacourt +3
Today's best language models still struggle with hallucinations: factually incorrect generations, which impede their ability to reliably retrieve information seen during training.…