long context deep comprehension - chunhualiao/public-docs GitHub Wiki
Fiction.liveBench is a benchmark designed to evaluate large language models (LLMs) on their ability to deeply comprehend long-form fiction narratives. Unlike traditional benchmarks that focus on short passages or factual retrieval, Fiction.liveBench emphasizes understanding complex storylines, character development, and thematic elements across extended texts.๎
Key Features
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Realistic Long-Form Content: Utilizes full-length fiction stories, often spanning tens of thousands of words, to assess models in scenarios that mirror real-world reading comprehension tasks.๎
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Deep Comprehension Tasks: Challenges models with questions that require synthesizing information from various parts of the text, such as analyzing character motivations, plot developments, and thematic nuances.๎
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Evaluation of Long-Range Dependencies: Tests the model's ability to maintain context and coherence over extended narratives, highlighting strengths and weaknesses in handling long-range dependencies.๎
Performance Insights
Recent evaluations have shown that even advanced models like LLaMA 4 face challenges with deep comprehension in long contexts. In contrast, models such as Google's Gemini 2.5 Pro have demonstrated superior performance, indicating advancements in handling extended narratives ๎cite๎turn0search10๎.๎
Comparison with Other Benchmarks
Fiction.liveBench complements other long-context benchmarks like XLยฒBench and NarrativeXL, which also focus on evaluating LLMs' abilities to process and understand extensive texts. However, Fiction.liveBench's emphasis on fiction narratives provides unique insights into a model's capacity for literary comprehension and narrative reasoning.๎
For more detailed information and access to the benchmark, you can visit the [Fiction.liveBench page](https://fiction.live/stories/Fiction-liveBench-Feb-21-2025/oQdzQvKHw8JyXbN87/home).