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Leave no document behind: Benchmarking long-context llms with extended multi-doc qa
Long-context modeling capabilities of Large Language Models (LLMs) have garnered
widespread attention, leading to the emergence of LLMs with ultra-context windows …
widespread attention, leading to the emergence of LLMs with ultra-context windows …
[PDF][PDF] Babilong: Testing the limits of llms with long context reasoning-in-a-haystack
In recent years, the input context sizes of large language models (LLMs) have increased
dramatically. However, existing evaluation methods have not kept pace, failing to …
dramatically. However, existing evaluation methods have not kept pace, failing to …
Long context is not long at all: A prospector of long-dependency data for large language models
Long-context modeling capabilities are important for large language models (LLMs) in
various applications. However, directly training LLMs with long context windows is …
various applications. However, directly training LLMs with long context windows is …
Evaluating Top-k RAG-based approach for Game Review Generation
P Chauhan, RK Sahani, S Datta, A Qadir… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Having access to public opinion for a particular product can be a cumbersome task. There
are multiple reviews for the same product. Some may be good or bad depending on the bias …
are multiple reviews for the same product. Some may be good or bad depending on the bias …
LCFO: Long context and long form output dataset and benchmarking
This paper presents the Long Context and Form Output (LCFO) benchmark, a novel
evaluation framework for assessing gradual summarization and summary expansion …
evaluation framework for assessing gradual summarization and summary expansion …
VisDoM: Multi-Document QA with Visually Rich Elements Using Multimodal Retrieval-Augmented Generation
Understanding information from a collection of multiple documents, particularly those with
visually rich elements, is important for document-grounded question answering. This paper …
visually rich elements, is important for document-grounded question answering. This paper …
Retrieval Or Holistic Understanding? Dolce: Differentiate Our Long Context Evaluation Tasks
Z Yang - arxiv preprint arxiv:2409.06338, 2024 - arxiv.org
We argue that there are two major distinct capabilities in long context understanding:
retrieval and holistic understanding. Understanding and further improving LLMs' long …
retrieval and holistic understanding. Understanding and further improving LLMs' long …