Pixtral 12B research paper by Mistral AI, 2024
Mistral AI · Multimodal and robotics · Oct 9, 2024 · 190 citations · 70 upvotes · unverified
What it shows
Pixtral-12B, a 12-billion-parameter multimodal language model, excels in both natural language and image understanding, surpassing larger models and introducing an open-source benchmark for evaluation.
By Pravesh Agrawal, Szymon Antoniak, Emma Bou Hanna and 34 more · arXiv 2410.07073 · PDF · Code
UnverifiedHugging Face's summary; not yet checked by hand.
More from Mistral AI
All 4Voxtral TTSVoxtral TTS is a multilingual text-to-speech model that generates natural speech from short reference audio using a hybrid architecture combining semantic token generation and flow-matching for acoustic tokens.
Mistral AI60 upvotesRead →Voxtral RealtimeVoxtral Realtime is a streaming speech recognition model trained end-to-end for sub-second latency with performance matching offline systems.
Mistral AI10 citations28 upvotesRead →Ministral 3The Ministral 3 series consists of parameter-efficient dense language models with three sizes (3B, 8B, 14B) and three variants per size, trained using cascade distillation for compute-constrained applications.
Mistral AI80 citations66 upvotesRead →
Other multimodal and robotics papers
TopicSegment AnythingA promptable model and a dataset of over a billion masks that cut out any object in any image.
Meta16.8k citations6 upvotesRead →BLIP-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 →BLIP: 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 →GPT-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 →SAM 3: Segment Anything with ConceptsSegment 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.
Meta1,466 citations138 upvotesRead →DeepSeek-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 →
About this paper
- Venue
- arXiv.org
- Citations
- 190, 23 influential · Semantic Scholar
- Upvotes
- 70 · Hugging Face
- Lab
- Mistral AI · on Companies · on Rounds · on Releases · on Releases
Changes
Citations rose from 185 to 190.
Influential citations rose from 21 to 23.
Citations rose from 176 to 185.
Citations rose from 175 to 176.
Citations rose from 174 to 175.
Influential citations rose from 19 to 21.
Citations rose from 173 to 174.
A first count of 19 influential citations.
A first count of 173 citations.
Found by the weekly Hugging Face scan; not yet checked by hand.