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Collections including paper arxiv:2510.12709

ByteDance Papers

ByteDance papers collection

Contrastive Learning for Many-to-many Multilingual Neural Machine Translation

Paper • 2105.09501 • Published May 20, 2021
Cross-modal Contrastive Learning for Speech Translation

Paper • 2205.02444 • Published May 5, 2022
ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs

Paper • 2210.03052 • Published Oct 6, 2022
Diffusion Glancing Transformer for Parallel Sequence to Sequence Learning

Paper • 2212.10240 • Published Dec 20, 2022 • 1

DLER: Doing Length pEnalty Right - Incentivizing More Intelligence per Token via Reinforcement Learning

Paper • 2510.15110 • Published Oct 16 • 15
PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model

Paper • 2510.14528 • Published Oct 16 • 94
Bee: A High-Quality Corpus and Full-Stack Suite to Unlock Advanced Fully Open MLLMs

Paper • 2510.13795 • Published Oct 15 • 56
UniME-V2: MLLM-as-a-Judge for Universal Multimodal Embedding Learning

Paper • 2510.13515 • Published Oct 15 • 11

UniME

Collection

UniME is a series of multimodal large language models trained for learning universal multimodal embedding. • 4 items • Updated May 16 • 4
GME: Improving Universal Multimodal Retrieval by Multimodal LLMs

Paper • 2412.16855 • Published Dec 22, 2024 • 5
VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks

Paper • 2410.05160 • Published Oct 7, 2024 • 4
VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents

Paper • 2507.04590 • Published Jul 7 • 16

about 14 hours ago

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 28
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Omni-modal Embedding Foundation Model

SAIL-Embedding Technical Report: Omni-modal Embedding Foundation Model

Paper • 2510.12709 • Published Oct 14 • 11

Representation Learning

End-to-End Vision Tokenizer Tuning

Paper • 2505.10562 • Published May 15 • 22
Global and Local Entailment Learning for Natural World Imagery

Paper • 2506.21476 • Published Jun 26 • 1
DINOv3

Paper • 2508.10104 • Published Aug 13 • 281
Reasoning Vectors: Transferring Chain-of-Thought Capabilities via Task Arithmetic

Paper • 2509.01363 • Published Sep 1 • 58

ByteDance Papers

ByteDance papers collection

Contrastive Learning for Many-to-many Multilingual Neural Machine Translation

Paper • 2105.09501 • Published May 20, 2021
Cross-modal Contrastive Learning for Speech Translation

Paper • 2205.02444 • Published May 5, 2022
ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs

Paper • 2210.03052 • Published Oct 6, 2022
Diffusion Glancing Transformer for Parallel Sequence to Sequence Learning

Paper • 2212.10240 • Published Dec 20, 2022 • 1

about 14 hours ago

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 28
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

DLER: Doing Length pEnalty Right - Incentivizing More Intelligence per Token via Reinforcement Learning

Paper • 2510.15110 • Published Oct 16 • 15
PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model

Paper • 2510.14528 • Published Oct 16 • 94
Bee: A High-Quality Corpus and Full-Stack Suite to Unlock Advanced Fully Open MLLMs

Paper • 2510.13795 • Published Oct 15 • 56
UniME-V2: MLLM-as-a-Judge for Universal Multimodal Embedding Learning

Paper • 2510.13515 • Published Oct 15 • 11

Omni-modal Embedding Foundation Model

SAIL-Embedding Technical Report: Omni-modal Embedding Foundation Model

Paper • 2510.12709 • Published Oct 14 • 11

UniME

Collection

UniME is a series of multimodal large language models trained for learning universal multimodal embedding. • 4 items • Updated May 16 • 4
GME: Improving Universal Multimodal Retrieval by Multimodal LLMs

Paper • 2412.16855 • Published Dec 22, 2024 • 5
VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks

Paper • 2410.05160 • Published Oct 7, 2024 • 4
VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents

Paper • 2507.04590 • Published Jul 7 • 16

Representation Learning

End-to-End Vision Tokenizer Tuning

Paper • 2505.10562 • Published May 15 • 22
Global and Local Entailment Learning for Natural World Imagery

Paper • 2506.21476 • Published Jun 26 • 1
DINOv3

Paper • 2508.10104 • Published Aug 13 • 281
Reasoning Vectors: Transferring Chain-of-Thought Capabilities via Task Arithmetic

Paper • 2509.01363 • Published Sep 1 • 58

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