SF20K competition results show top AI models reach 65.7% accuracy on story-level video QA using amateur films, with information selection and reasoning structure as the main bottlenecks rather than model size, well below human performance of 91.7%.
Introducing GPT-4.1 in the API, 2025
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MaxShapley computes fair document attributions in generative QA by reducing Shapley value calculation to polynomial time via a max-sum utility, matching exact Shapley quality on HotPotQA, MuSiQUE, and MS MARCO while using up to 9x fewer resources.
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SF20K Competition 2025: Summary and findings
SF20K competition results show top AI models reach 65.7% accuracy on story-level video QA using amateur films, with information selection and reasoning structure as the main bottlenecks rather than model size, well below human performance of 91.7%.
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MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution
MaxShapley computes fair document attributions in generative QA by reducing Shapley value calculation to polynomial time via a max-sum utility, matching exact Shapley quality on HotPotQA, MuSiQUE, and MS MARCO while using up to 9x fewer resources.