3 papers
cs.CL2025
Oolong: Evaluating Long Context Reasoning and Aggregation Capabilities
Amanda Bertsch, Adithya Pratapa, Teruko Mitamura +2
As model context lengths continue to grow, concerns about whether models effectively use the full context length have persisted. While several carefully designed long-context evalu…
cs.CL2025
Estimating Optimal Context Length for Hybrid Retrieval-augmented Multi-document Summarization
Adithya Pratapa, Teruko Mitamura
Recent advances in long-context reasoning abilities of language models led to interesting applications in large-scale multi-document summarization. However, prior work has shown th…
cs.CL2025
Scaling Multi-Document Event Summarization: Evaluating Compression vs. Full-Text Approaches
Adithya Pratapa, Teruko Mitamura
Automatically summarizing large text collections is a valuable tool for document research, with applications in journalism, academic research, legal work, and many other fields. In…