1 citations · 1 across the 4 of their papers we have counts for
5 papers
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…
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…
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…
Can AI Examine Novelty of Patents?: Novelty Evaluation Based on the Correspondence between Patent Claim and Prior Art
Hayato Ikoma, Teruko Mitamura
Assessing the novelty of patent claims is a critical yet challenging task traditionally performed by patent examiners. While advancements in NLP have enabled progress in various pa…
What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions
Sang Keun Choe, Hwijeen Ahn, Juhan Bae +11
Large language models (LLMs) are trained on a vast amount of human-written data, but data providers often remain uncredited. In response to this issue, data valuation (or data attr…