6 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CL2024
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…
cs.CL2024★ 6 cited
The Hallucinations Leaderboard -- An Open Effort to Measure Hallucinations in Large Language Models
Giwon Hong, Aryo Pradipta Gema, Rohit Saxena +8
Large Language Models (LLMs) have transformed the Natural Language Processing (NLP) landscape with their remarkable ability to understand and generate human-like text. However, the…
cs.CL2024
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…