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@@ -275,8 +275,8 @@ texts = [item["text"] for item in result["results"]]
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  MOSS-VL-Base-0408 is a pretrained base checkpoint, and we are actively improving several core capabilities for future iterations:
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- - 📄 Stronger OCR, Especially for Long Documents — We plan to further improve text recognition, document parsing, and long-document understanding. A key focus is achieving near-lossless information extraction for extremely long and structurally complex inputs, such as accurately parsing texts, tables, and mathematical layouts from multi-page academic papers (dozens of pages) or dense PDF reports without degrading context or structural integrity.
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- - 🎬 Expanded Long-Video Understanding — We aim to significantly extend the model's capacity for long-form video comprehension. This includes advancing temporal reasoning and cross-frame event tracking to support the continuous analysis of videos lasting several hours to dozens of hours—such as full-length movies, lengthy meetings, or extended surveillance streamsenabling robust retrieval and understanding over ultra-long visual contexts.
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  > [!NOTE]
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  > We expect future releases to continue strengthening the base model itself while also enabling stronger downstream aligned variants built on top of it.
 
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  MOSS-VL-Base-0408 is a pretrained base checkpoint, and we are actively improving several core capabilities for future iterations:
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+ - 📄 **Stronger OCR, Especially for Long Documents** — We plan to further improve text recognition, document parsing, and long-document understanding. A key focus is achieving near-lossless information extraction and understanding for extremely long and structurally complex inputs, such as accurately parsing texts, tables, and mathematical layouts from multi-page academic papers (dozens of pages) or dense PDF reports without degrading context or structural integrity.
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+ - 🎬 **Expanded Extremely Long Video Understanding** — We aim to significantly extend the model's capacity for comprehending extremely long videos spanning several hours to dozens of hours. This includes advancing temporal reasoning and cross-frame event tracking for continuous analysis of full-length movies, lengthy meetings, or extended surveillance streams, enabling robust retrieval and understanding over ultra-long visual contexts.
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  > [!NOTE]
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  > We expect future releases to continue strengthening the base model itself while also enabling stronger downstream aligned variants built on top of it.