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 **SEEM_v1:** Supporting Multiple Interactive objects training and inference
 
 ## :rocket: Updates
-* **[2023.07.27]** :roller_coaster: We are excited to release our [X-Decoder](https://github.com/microsoft/X-Decoder) training code! We will release its descendant SEEM training code very soon!
+* **[2023.10.04]** We are excited to release :white_check_mark: [training/evaluation/demo code](https://github.com/UX-Decoder/Segment-Everything-Everywhere-All-At-Once/edit/v1.0/README.md#bookmark_tabs-catalog), :white_check_mark: [new checkpoints](https://github.com/UX-Decoder/Segment-Everything-Everywhere-All-At-Once/edit/v1.0/README.md#bookmark_tabs-catalog), and :white_check_mark: [comprehensive readmes](https://github.com/UX-Decoder/Segment-Everything-Everywhere-All-At-Once/edit/v1.0/README.md#bookmark_tabs-catalog) for ***both X-Decoder and SEEM***!
+* **[2023.07.27]** We are excited to release our [X-Decoder](https://github.com/microsoft/X-Decoder) training code! We will release its descendant SEEM training code very soon!
 * **[2023.07.10]** We release [Semantic-SAM](https://github.com/UX-Decoder/Semantic-SAM), a universal image segmentation model to enable segment and recognize anything at any desired granularity. Code and checkpoint are available!
 * **[2023.05.02]** We have released the [SEEM Focal-L](https://projects4jw.blob.core.windows.net/x-decoder/release/seem_focall_v1.pt) and [X-Decoder Focal-L](https://projects4jw.blob.core.windows.net/x-decoder/release/xdecoder_focall_last.pt) checkpoints and [configs](https://github.com/UX-Decoder/Segment-Everything-Everywhere-All-At-Once/blob/main/demo_code/configs/seem/seem_focall_lang.yaml)!
 * **[2023.04.28]** We have updated the [ArXiv](https://arxiv.org/pdf/2304.06718.pdf) that shows *better interactive segmentation results than SAM*, which trained on x50 more data than us!