Update README.md

README.md

@@ -13,24 +13,32 @@ We value:
 - using public and open corpora
 - open-source training and evaluation code.
 
-In this organization, you can find RoLLM models, based on different underlying models and in different flavours (i.e., foundational, instruct, or chat variants). There are currently four model collections:
+In this organization, you can find RoLLM models, based on different underlying models and in different flavours (i.e., foundational, instruct, or chat variants):
 - RoLlama2: Romanian models based on Llama2
 - RoMistral: Romanian models based on Mistral
 - RoLlama3: Romanian models based on Llama3
 - RoLlama3.1: Romanian models based on Llama3.1
 - RoGemma: Romanian models based on Gemma
 - RoGemma2: Romanian models based on Gemma2
+- RoLlava: Romanian models based on Llava
+- RoQwen2-VL: Romanian models based on Qwen2-VL
+- RoQwen2.5-VL: Romanian models based on Qwen2.5-VL
+- RoQwen3-VL: Romanian models based on Qwen3-VL
+- RoGemma3: Romanian models based on Gemma3
 
 
-Furthermore, here you can find data used to train and evaluate LLMs in Romanian. Currently, there are three data collections:
+Furthermore, here you can find data used to train and evaluate LLMs & VLMs in Romanian. Currently, there are four data collections:
+- Pretraining dataset: Romanian pretraining quality-filtered data
 - SFT datasets: data used for supervised (instruction) finetuning
 - Alignment datasets: data used mainly for Direct Preference Optimization (DPO)
-- Evaluation datasets: data used for evaluating LLM in Romanian
+- Evaluation datasets: data used for evaluating models in Romanian
 
-See details in [https://arxiv.org/abs/2406.18266](https://arxiv.org/abs/2406.18266) and [https://arxiv.org/abs/2405.07703](https://arxiv.org/abs/2405.07703).
-
-- 2025-04-23: we increased the datasets used for supervised finetuning with high-quality data generated using Magpie ([RoMagpie-Reasoning](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_magpie_reasoning) and [RoMagpie-Pro-MT](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_magpie_mt)), and greatly increase the size of the alignment dataset by adding high-quality datasets ([RoUltraFeedback](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_ultrafeedback), [RoMagpie-DPO](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_magpie), [RoArgillaMagpieUltra](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_argilla_magpie) and [RoHelpSteer2](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_helpsteer2))
+See details in [https://arxiv.org/abs/2406.18266](https://arxiv.org/abs/2406.18266) and [https://arxiv.org/abs/2605.31401](https://arxiv.org/abs/2605.31401).
 
+- 23-04-2025: we increased the datasets used for supervised finetuning with high-quality data generated using Magpie ([RoMagpie-Reasoning](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_magpie_reasoning) and [RoMagpie-Pro-MT](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_magpie_mt)), and greatly increase the size of the alignment dataset by adding high-quality datasets ([RoUltraFeedback](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_ultrafeedback), [RoMagpie-DPO](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_magpie), [RoArgillaMagpieUltra](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_argilla_magpie) and [RoHelpSteer2](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_helpsteer2))
+- 28-11-2025: we release augmented pretraining data and quality classifier
+- 05-06-2026: we release RoVLMs together with training and evaluation data
+- 
 We encourage the community to engage in discussions (to provide feedback, ask questions, or make improvement suggestions) in Hugging Face or GitHub. 
 
 We will also organize physical meetings (announced in advance) to brainstorm ideas, roadmap, and other technical aspects.