1 citations · 1 across the 6 of their papers we have counts for
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MIXAR: Scaling Autoregressive Pixel-based Language Models to Multiple Languages and Scripts
Chen Hu, Yintao Tai, Antonio Vergari +2
Pixel-based language models are gaining momentum as alternatives to traditional token-based approaches, promising to circumvent tokenization challenges; however, existing models re…
Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books
Argyrios Papoudakis, Mirella Lapata, Frank Keller
Character description generation is an important capability for narrative-focused applications such as summarization, story analysis, and character-driven simulations. However, gen…
End-to-End Long Document Summarization using Gradient Caching
Rohit Saxena, Hao Tang, Frank Keller
Training transformer-based encoder-decoder models for long document summarization poses a significant challenge due to the quadratic memory consumption during training. Several app…
MovieSum: An Abstractive Summarization Dataset for Movie Screenplays
Rohit Saxena, Frank Keller
Movie screenplay summarization is challenging, as it requires an understanding of long input contexts and various elements unique to movies. Large language models have shown signif…
Select and Summarize: Scene Saliency for Movie Script Summarization
Rohit Saxena, Frank Keller
Abstractive summarization for long-form narrative texts such as movie scripts is challenging due to the computational and memory constraints of current language models. A movie scr…