{"schema_version":"onlylabs.public_signal.v1","title":"ByteDance (Doubao/Seed) Model: ByteDance-Seed/Cola-DLM","description":"ByteDance (Doubao/Seed) model signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/a6b59621-a4bd-4f69-a1c7-81dd4c45f526","json_url":"https://onlylabs.fyi/signals/a6b59621-a4bd-4f69-a1c7-81dd4c45f526/signal.json","generated_at":"2026-06-11T02:40:51.343463+00:00","org":{"slug":"bytedance","name":"ByteDance (Doubao/Seed)","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/bytedance","dossier_json_url":"https://onlylabs.fyi/labs/bytedance/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/a6b59621-a4bd-4f69-a1c7-81dd4c45f526","signal_json":"https://onlylabs.fyi/signals/a6b59621-a4bd-4f69-a1c7-81dd4c45f526/signal.json","source":"https://huggingface.co/ByteDance-Seed/Cola-DLM","lab_dossier":"https://onlylabs.fyi/labs/bytedance","lab_dossier_json":"https://onlylabs.fyi/labs/bytedance/dossier.json","analysis":"https://onlylabs.fyi/analysis/bytedance","analysis_json":"https://onlylabs.fyi/analysis/bytedance/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/bytedance/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":"https://onlylabs.fyi/topics/releases","topic_signals_json":"https://onlylabs.fyi/topics/releases/signals.json","topic_feed":"https://onlylabs.fyi/topics/releases/feed.xml","data_business":null},"answer_pack":{"answer":"ByteDance (Doubao/Seed) published ByteDance-Seed/Cola-DLM. 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It combines a Text VAE with a block-causal Diffusion Transformer (DiT) prior: the VAE maps text into continuous latent sequences and decodes latents back to tokens, while the DiT performs latent prior transport through Flow Matching. This model repository contains the HuggingFace-format checkpoint for the paper **Continuous Latent Diffusion Language Model**. 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It combines a Text VAE with a block-causal Diffusion Transformer (DiT) prior: the VAE maps text into continuous latent sequences and decodes latents back to tokens, while the DiT performs latent prior transport through Flow Matching. This model repository contains the HuggingFace-format checkpoint for the paper **Continuous Latent Diffusion Language Model**. 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