🔹 Title: UniME-V2: MLLM-as-a-Judge for Universal Multimodal Embedding Learning
🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13515
• PDF: https://arxiv.org/pdf/2510.13515
• Project Page: https://garygutc.github.io/UniME-v2/
• Github: https://github.com/GaryGuTC/UniME-v2
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🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13515
• PDF: https://arxiv.org/pdf/2510.13515
• Project Page: https://garygutc.github.io/UniME-v2/
• Github: https://github.com/GaryGuTC/UniME-v2
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🔹 Title: ParallelBench: Understanding the Trade-offs of Parallel Decoding in Diffusion LLMs
🔹 Publication Date: Published on Oct 6
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.04767
• PDF: https://arxiv.org/pdf/2510.04767
• Project Page: https://parallelbench.github.io
• Github: https://github.com/furiosa-ai/ParallelBench
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🔹 Publication Date: Published on Oct 6
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.04767
• PDF: https://arxiv.org/pdf/2510.04767
• Project Page: https://parallelbench.github.io
• Github: https://github.com/furiosa-ai/ParallelBench
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🔹 Title: CVD-STORM: Cross-View Video Diffusion with Spatial-Temporal Reconstruction Model for Autonomous Driving
🔹 Publication Date: Published on Oct 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07944
• PDF: https://arxiv.org/pdf/2510.07944
• Project Page: https://sensetime-fvg.github.io/CVD-STORM/
• Github: https://github.com/SenseTime-FVG/OpenDWM
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🔹 Publication Date: Published on Oct 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07944
• PDF: https://arxiv.org/pdf/2510.07944
• Project Page: https://sensetime-fvg.github.io/CVD-STORM/
• Github: https://github.com/SenseTime-FVG/OpenDWM
🔹 Datasets citing this paper:
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🔹 Title: Revisiting Model Interpolation for Efficient Reasoning
🔹 Publication Date: Published on Oct 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10977
• PDF: https://arxiv.org/pdf/2510.10977
• Github: https://github.com/wutaiqiang/MI
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🔹 Publication Date: Published on Oct 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10977
• PDF: https://arxiv.org/pdf/2510.10977
• Github: https://github.com/wutaiqiang/MI
🔹 Datasets citing this paper:
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🔹 Title: Bee: A High-Quality Corpus and Full-Stack Suite to Unlock Advanced Fully Open MLLMs
🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13795
• PDF: https://arxiv.org/pdf/2510.13795
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🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13795
• PDF: https://arxiv.org/pdf/2510.13795
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🔹 Title: NOSA: Native and Offloadable Sparse Attention
🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13602
• PDF: https://arxiv.org/pdf/2510.13602
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🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13602
• PDF: https://arxiv.org/pdf/2510.13602
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🔹 Title: CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
🔹 Publication Date: Published on Oct 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.12560
• PDF: https://arxiv.org/pdf/2510.12560
• Project Page: https://seu-zxj.github.io/CoIRL-AD/
• Github: https://github.com/SEU-zxj/CoIRL-AD
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🔹 Publication Date: Published on Oct 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.12560
• PDF: https://arxiv.org/pdf/2510.12560
• Project Page: https://seu-zxj.github.io/CoIRL-AD/
• Github: https://github.com/SEU-zxj/CoIRL-AD
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🔹 Title: MTSQL-R1: Towards Long-Horizon Multi-Turn Text-to-SQL via Agentic Training
🔹 Publication Date: Published on Oct 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.12831
• PDF: https://arxiv.org/pdf/2510.12831
• Github: https://github.com/taichengguo/MTSQL-R1
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🔹 Publication Date: Published on Oct 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.12831
• PDF: https://arxiv.org/pdf/2510.12831
• Github: https://github.com/taichengguo/MTSQL-R1
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🔹 Title: HyperAgent: Leveraging Hypergraphs for Topology Optimization in Multi-Agent Communication
🔹 Publication Date: Published on Oct 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10611
• PDF: https://arxiv.org/pdf/2510.10611
🔹 Datasets citing this paper:
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🔹 Publication Date: Published on Oct 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10611
• PDF: https://arxiv.org/pdf/2510.10611
🔹 Datasets citing this paper:
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🔹 Title: GraphTracer: Graph-Guided Failure Tracing in LLM Agents for Robust Multi-Turn Deep Search
🔹 Publication Date: Published on Oct 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10581
• PDF: https://arxiv.org/pdf/2510.10581
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🔹 Publication Date: Published on Oct 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10581
• PDF: https://arxiv.org/pdf/2510.10581
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🔹 Title: InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy
🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13778
• PDF: https://arxiv.org/pdf/2510.13778
• Project Page: https://internrobotics.github.io/internvla-m1.github.io/
• Github: https://github.com/InternRobotics/InternVLA-M1
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🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13778
• PDF: https://arxiv.org/pdf/2510.13778
• Project Page: https://internrobotics.github.io/internvla-m1.github.io/
• Github: https://github.com/InternRobotics/InternVLA-M1
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🔹 Title: Uni-MMMU: A Massive Multi-discipline Multimodal Unified Benchmark
🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13759
• PDF: https://arxiv.org/pdf/2510.13759
🔹 Datasets citing this paper:
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🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13759
• PDF: https://arxiv.org/pdf/2510.13759
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🔹 Title: LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models
🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13626
• PDF: https://arxiv.org/pdf/2510.13626
• Project Page: https://sylvestf.github.io/LIBERO-plus/
• Github: https://github.com/sylvestf/LIBERO-plus
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🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13626
• PDF: https://arxiv.org/pdf/2510.13626
• Project Page: https://sylvestf.github.io/LIBERO-plus/
• Github: https://github.com/sylvestf/LIBERO-plus
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🔹 Title: UniMoE-Audio: Unified Speech and Music Generation with Dynamic-Capacity MoE
🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13344
• PDF: https://arxiv.org/pdf/2510.13344
• Github: https://github.com/HITsz-TMG/Uni-MoE/blob/master/UniMoE-Audio
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🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13344
• PDF: https://arxiv.org/pdf/2510.13344
• Github: https://github.com/HITsz-TMG/Uni-MoE/blob/master/UniMoE-Audio
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🔹 Title: Direct Multi-Token Decoding
🔹 Publication Date: Published on Oct 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.11958
• PDF: https://arxiv.org/pdf/2510.11958
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🔹 Publication Date: Published on Oct 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.11958
• PDF: https://arxiv.org/pdf/2510.11958
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🔹 Title: Attention Illuminates LLM Reasoning: The Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization
🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13554
• PDF: https://arxiv.org/pdf/2510.13554
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🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13554
• PDF: https://arxiv.org/pdf/2510.13554
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🔹 Title: FG-CLIP 2: A Bilingual Fine-grained Vision-Language Alignment Model
🔹 Publication Date: Published on Oct 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10921
• PDF: https://arxiv.org/pdf/2510.10921
• Project Page: https://360cvgroup.github.io/FG-CLIP/
🔹 Datasets citing this paper:
• https://huggingface.co/datasets/qihoo360/DCI-CN
• https://huggingface.co/datasets/qihoo360/BoxClass-CN
• https://huggingface.co/datasets/qihoo360/LIT-CN
• https://huggingface.co/datasets/qihoo360/DOCCI-CN
🔹 Spaces citing this paper:
• https://huggingface.co/spaces/qihoo360/FG-CLIP2-Retrieval-demo
• https://huggingface.co/spaces/qihoo360/FG-CLIP2-Densefeature-demo
==================================
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🔹 Publication Date: Published on Oct 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10921
• PDF: https://arxiv.org/pdf/2510.10921
• Project Page: https://360cvgroup.github.io/FG-CLIP/
🔹 Datasets citing this paper:
• https://huggingface.co/datasets/qihoo360/DCI-CN
• https://huggingface.co/datasets/qihoo360/BoxClass-CN
• https://huggingface.co/datasets/qihoo360/LIT-CN
• https://huggingface.co/datasets/qihoo360/DOCCI-CN
🔹 Spaces citing this paper:
• https://huggingface.co/spaces/qihoo360/FG-CLIP2-Retrieval-demo
• https://huggingface.co/spaces/qihoo360/FG-CLIP2-Densefeature-demo
==================================
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🔹 Title: X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model
🔹 Publication Date: Published on Oct 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10274
• PDF: https://arxiv.org/pdf/2510.10274
• Project Page: https://thu-air-dream.github.io/X-VLA/
• Github: https://github.com/2toinf/X-VLA.git
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🔹 Publication Date: Published on Oct 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10274
• PDF: https://arxiv.org/pdf/2510.10274
• Project Page: https://thu-air-dream.github.io/X-VLA/
• Github: https://github.com/2toinf/X-VLA.git
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🔹 Title: Universal Image Restoration Pre-training via Masked Degradation Classification
🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13282
• PDF: https://arxiv.org/pdf/2510.13282
• Project Page: https://github.com/MILab-PKU/MaskDCPT
• Github: https://github.com/MILab-PKU/MaskDCPT
🔹 Datasets citing this paper:
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🔹 Publication Date: Published on Oct 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13282
• PDF: https://arxiv.org/pdf/2510.13282
• Project Page: https://github.com/MILab-PKU/MaskDCPT
• Github: https://github.com/MILab-PKU/MaskDCPT
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❤1
Contribute with us to expand the services offered in our channel
We plan to use an advanced AI model to add more information about the most prominent events, models, and articles released and provide explanations.
This requires preparing an infrastructure for our server and purchasing an API for an AI model.
Contribute to the development of our community with us
Contact me @husseinsheikho
We plan to use an advanced AI model to add more information about the most prominent events, models, and articles released and provide explanations.
This requires preparing an infrastructure for our server and purchasing an API for an AI model.
Contribute to the development of our community with us
Contact me @husseinsheikho
ML Research Hub pinned «Contribute with us to expand the services offered in our channel We plan to use an advanced AI model to add more information about the most prominent events, models, and articles released and provide explanations. This requires preparing an infrastructure…»