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SAM 3: Segment Anything with Concepts research paper by Meta, 2025

Meta · Multimodal and robotics · Nov 20, 2025 · 1,466 citations · 138 upvotes · unverified

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What it shows

Segment Anything Model 3 achieves state-of-the-art performance in promptable concept segmentation and tracking by leveraging a unified model architecture with decoupled recognition and localization.

By Nicolas Carion, Laura Gustafson, Yuan-Ting Hu and 35 more · arXiv 2511.16719 · PDF · Code

UnverifiedHugging Face's summary; not yet checked by hand.

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Other multimodal and robotics papers

Topic
Multimodal and roboticsJan 30, 2023BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language ModelsBLIP-2 efficiently pre-trains vision-language models using off-the-shelf frozen encoders and decoders, achieving state-of-the-art performance with fewer parameters.Salesforce9,805 citations3 upvotesRead →Multimodal and roboticsJan 28, 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and GenerationBLIP, a Vision-Language Pre-training framework, improves performance across both understanding and generation tasks by bootstrapping captions from noisy web data, achieving state-of-the-art results on image-text retrieval, image captioning, and VQA, and showing strong generalization to video-language tasks.Salesforce7,655 citations5 upvotesRead →Multimodal and roboticsUnverifiedOct 25, 2024GPT-4o System CardGPT-4o is an omnimodal autoregressive model trained to handle text, audio, image, and video inputs, offering high-performance outputs across these modalities, with particular strengths in vision and audio.OpenAI5,388 citations88 upvotesRead →Multimodal and roboticsUnverifiedMar 8, 2024DeepSeek-VL: Towards Real-World Vision-Language UnderstandingDeepSeek-VL is an open-source vision-language model that achieves state-of-the-art performance in real-world applications by combining a hybrid vision encoder with effective pretraining strategies to preserve language model capabilities.DeepSeek939 citations49 upvotesRead →Multimodal and roboticsUnverifiedOct 17, 2024Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and GenerationJanus, an autoregressive framework with separate visual encoding pathways within a unified transformer architecture, enhances performance in unified multimodal understanding and generation.DeepSeek525 citations37 upvotesRead →Multimodal and roboticsUnverifiedSep 26, 2025LongLive: Real-time Interactive Long Video GenerationLongLive is a frame-level autoregressive framework for real-time and interactive long video generation, addressing efficiency and quality challenges through causal attention, KV-recache, streaming long tuning, and short window attention.NVIDIA297 citations191 upvotesRead →
About this paper
Venue
arXiv.org
Citations
1,466, 237 influential · Semantic Scholar
Upvotes
138 · Hugging Face
Lab
Meta · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

CitationsNov 9, 2026Influential citations rose from 223 to 237.
CitationsNov 9, 2026Citations rose from 1,386 to 1,466.
CitationsNov 2, 2026Influential citations rose from 188 to 223.
CitationsNov 2, 2026Citations rose from 1,198 to 1,386.
CitationsOct 12, 2026Influential citations rose from 175 to 188.
CitationsOct 12, 2026Citations rose from 1,105 to 1,198.
CitationsOct 5, 2026Influential citations rose from 158 to 175.
CitationsOct 5, 2026Citations rose from 1,024 to 1,105.
CitationsSep 28, 2026Influential citations rose from 153 to 158.
CitationsSep 28, 2026Citations rose from 999 to 1,024.
CitationsSep 25, 2026A first count of 153 influential citations.
CitationsSep 25, 2026A first count of 999 citations.
New paperSep 25, 2026Found by the weekly Hugging Face scan; not yet checked by hand.