πΉ Title: VLM-Guided Adaptive Negative Prompting for Creative Generation
πΉ Publication Date: Published on Oct 12
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.10715
β’ PDF: https://arxiv.org/pdf/2510.10715
β’ Github: https://shelley-golan.github.io/VLM-Guided-Creative-Generation/
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πΉ Publication Date: Published on Oct 12
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.10715
β’ PDF: https://arxiv.org/pdf/2510.10715
β’ Github: https://shelley-golan.github.io/VLM-Guided-Creative-Generation/
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π€π§ Thinking with Camera 2.0: A Powerful Multimodal Model for Camera-Centric Understanding and Generation
ποΈ 14 Oct 2025
π AI News & Trends
In the rapidly evolving field of multimodal AI, bridging gaps between vision, language and geometry is one of the frontier challenges. Traditional vision-language models excel at describing what is in an image βa cat on a sofaβ βa red car on the roadβ but struggle to reason about how the image was captured: the cameraβs ...
#MultimodalAI #CameraCentricUnderstanding #VisionLanguageModels #AIResearch #ComputerVision #GenerativeModels
ποΈ 14 Oct 2025
π AI News & Trends
In the rapidly evolving field of multimodal AI, bridging gaps between vision, language and geometry is one of the frontier challenges. Traditional vision-language models excel at describing what is in an image βa cat on a sofaβ βa red car on the roadβ but struggle to reason about how the image was captured: the cameraβs ...
#MultimodalAI #CameraCentricUnderstanding #VisionLanguageModels #AIResearch #ComputerVision #GenerativeModels
π€π§ Granite-Speech-3.3-8B: IBMβs Next-Gen Speech-Language Model for Enterprise AI
ποΈ 14 Oct 2025
π AI News & Trends
In the fast-growing field of speech and language AI, IBM continues to make strides with its Granite model family , a suite of open enterprise-grade AI models that combine accuracy, safety and efficiency. The latest addition to this ecosystem, Granite-Speech-3.3-8B marks a significant milestone in automatic speech recognition (ASR) and speech translation (AST) technology. Released ...
#SpeechAI #LanguageModel #EnterpriseAI #ASR #SpeechTranslation #GraniteModel
ποΈ 14 Oct 2025
π AI News & Trends
In the fast-growing field of speech and language AI, IBM continues to make strides with its Granite model family , a suite of open enterprise-grade AI models that combine accuracy, safety and efficiency. The latest addition to this ecosystem, Granite-Speech-3.3-8B marks a significant milestone in automatic speech recognition (ASR) and speech translation (AST) technology. Released ...
#SpeechAI #LanguageModel #EnterpriseAI #ASR #SpeechTranslation #GraniteModel
π€π§ LLaMAX2 by Nanjing University, HKU, CMU & Shanghai AI Lab: A Breakthrough in Translation-Enhanced Reasoning Models
ποΈ 14 Oct 2025
π AI News & Trends
The world of large language models (LLMs) has evolved rapidly, producing advanced systems capable of reasoning, problem-solving, and creative text generation. However, a persistent challenge has been balancing translation quality with reasoning ability. Most translation-enhanced models excel in linguistic diversity but falter in logical reasoning or coding tasks. Addressing this crucial gap, the research paper ...
#LLaMAX2 #TranslationEnhanced #ReasoningModels #LargeLanguageModels #NanjingUniversity #HKU
ποΈ 14 Oct 2025
π AI News & Trends
The world of large language models (LLMs) has evolved rapidly, producing advanced systems capable of reasoning, problem-solving, and creative text generation. However, a persistent challenge has been balancing translation quality with reasoning ability. Most translation-enhanced models excel in linguistic diversity but falter in logical reasoning or coding tasks. Addressing this crucial gap, the research paper ...
#LLaMAX2 #TranslationEnhanced #ReasoningModels #LargeLanguageModels #NanjingUniversity #HKU
π€π§ Diffusion Transformers with Representation Autoencoders (RAE): The Next Leap in Generative AI
ποΈ 14 Oct 2025
π AI News & Trends
Diffusion Transformers (DiTs) have revolutionized image and video generation enabling stunningly realistic outputs in systems like Stable Diffusion and Imagen. However, despite innovations in transformer architectures and training methods, one crucial element of the diffusion pipeline has remained largely stagnant- the autoencoder that defines the latent space. Most current diffusion models still depend on Variational ...
#DiffusionTransformers #RAE #GenerativeAI #StableDiffusion #Imagen #LatentSpace
ποΈ 14 Oct 2025
π AI News & Trends
Diffusion Transformers (DiTs) have revolutionized image and video generation enabling stunningly realistic outputs in systems like Stable Diffusion and Imagen. However, despite innovations in transformer architectures and training methods, one crucial element of the diffusion pipeline has remained largely stagnant- the autoencoder that defines the latent space. Most current diffusion models still depend on Variational ...
#DiffusionTransformers #RAE #GenerativeAI #StableDiffusion #Imagen #LatentSpace
πΉ Title: FlashVSR: Towards Real-Time Diffusion-Based Streaming Video Super-Resolution
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12747
β’ PDF: https://arxiv.org/pdf/2510.12747
β’ Project Page: https://zhuang2002.github.io/FlashVSR/
β’ Github: https://github.com/OpenImagingLab/FlashVSR
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12747
β’ PDF: https://arxiv.org/pdf/2510.12747
β’ Project Page: https://zhuang2002.github.io/FlashVSR/
β’ Github: https://github.com/OpenImagingLab/FlashVSR
πΉ Datasets citing this paper:
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πΉ Title: Memory as Action: Autonomous Context Curation for Long-Horizon Agentic Tasks
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12635
β’ PDF: https://arxiv.org/pdf/2510.12635
πΉ Datasets citing this paper:
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πΉ Spaces citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12635
β’ PDF: https://arxiv.org/pdf/2510.12635
πΉ Datasets citing this paper:
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πΉ Title: Advancing End-to-End Pixel Space Generative Modeling via Self-supervised Pre-training
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12586
β’ PDF: https://arxiv.org/pdf/2510.12586
β’ Github: https://github.com/AMAP-ML/EPG
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12586
β’ PDF: https://arxiv.org/pdf/2510.12586
β’ Github: https://github.com/AMAP-ML/EPG
πΉ Datasets citing this paper:
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πΉ Title: LLM Reasoning for Machine Translation: Synthetic Data Generation over Thinking Tokens
πΉ Publication Date: Published on Oct 13
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.11919
β’ PDF: https://arxiv.org/pdf/2510.11919
β’ Github: https://github.com/ArmelRandy/llm-reasoning-mt
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 13
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.11919
β’ PDF: https://arxiv.org/pdf/2510.11919
β’ Github: https://github.com/ArmelRandy/llm-reasoning-mt
πΉ Datasets citing this paper:
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πΉ Spaces citing this paper:
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πΉ Title: DeepMMSearch-R1: Empowering Multimodal LLMs in Multimodal Web Search
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12801
β’ PDF: https://arxiv.org/pdf/2510.12801
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12801
β’ PDF: https://arxiv.org/pdf/2510.12801
πΉ Datasets citing this paper:
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πΉ Title: Detect Anything via Next Point Prediction
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12798
β’ PDF: https://arxiv.org/pdf/2510.12798
β’ Project Page: https://rex-omni.github.io/
β’ Github: https://github.com/IDEA-Research/Rex-Omni
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12798
β’ PDF: https://arxiv.org/pdf/2510.12798
β’ Project Page: https://rex-omni.github.io/
β’ Github: https://github.com/IDEA-Research/Rex-Omni
πΉ Datasets citing this paper:
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πΉ Title: UniFusion: Vision-Language Model as Unified Encoder in Image Generation
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12789
β’ PDF: https://arxiv.org/pdf/2510.12789
β’ Project Page: https://thekevinli.github.io/unifusion/
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12789
β’ PDF: https://arxiv.org/pdf/2510.12789
β’ Project Page: https://thekevinli.github.io/unifusion/
πΉ Datasets citing this paper:
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πΉ Title: DITING: A Multi-Agent Evaluation Framework for Benchmarking Web Novel Translation
πΉ Publication Date: Published on Oct 10
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.09116
β’ PDF: https://arxiv.org/pdf/2510.09116
β’ Github: https://github.com/WHUNextGen/DITING
πΉ Datasets citing this paper:
β’ https://huggingface.co/datasets/NextGenWhu/DITING
πΉ Spaces citing this paper:
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πΉ Publication Date: Published on Oct 10
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.09116
β’ PDF: https://arxiv.org/pdf/2510.09116
β’ Github: https://github.com/WHUNextGen/DITING
πΉ Datasets citing this paper:
β’ https://huggingface.co/datasets/NextGenWhu/DITING
πΉ Spaces citing this paper:
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πΉ Title: Scaling Language-Centric Omnimodal Representation Learning
πΉ Publication Date: Published on Oct 13
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.11693
β’ PDF: https://arxiv.org/pdf/2510.11693
β’ Project Page: https://huggingface.co/LCO-Embedding
β’ Github: https://github.com/LCO-Embedding/LCO-Embedding
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 13
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.11693
β’ PDF: https://arxiv.org/pdf/2510.11693
β’ Project Page: https://huggingface.co/LCO-Embedding
β’ Github: https://github.com/LCO-Embedding/LCO-Embedding
πΉ Datasets citing this paper:
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πΉ Title: A Survey of Vibe Coding with Large Language Models
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12399
β’ PDF: https://arxiv.org/pdf/2510.12399
β’ Github: https://github.com/YuyaoGe/Awesome-Vibe-Coding
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12399
β’ PDF: https://arxiv.org/pdf/2510.12399
β’ Github: https://github.com/YuyaoGe/Awesome-Vibe-Coding
πΉ Datasets citing this paper:
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πΉ Title: ERA: Transforming VLMs into Embodied Agents via Embodied Prior Learning and Online Reinforcement Learning
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12693
β’ PDF: https://arxiv.org/pdf/2510.12693
β’ Project Page: https://embodied-reasoning-agent.github.io
β’ Github: https://embodied-reasoning-agent.github.io
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12693
β’ PDF: https://arxiv.org/pdf/2510.12693
β’ Project Page: https://embodied-reasoning-agent.github.io
β’ Github: https://embodied-reasoning-agent.github.io
πΉ Datasets citing this paper:
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πΉ Title: Boundary-Guided Policy Optimization for Memory-efficient RL of Diffusion Large Language Models
πΉ Publication Date: Published on Oct 13
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/pdf/2510.11683
β’ PDF: https://arxiv.org/pdf/2510.11683
β’ Github: https://github.com/THU-KEG/BGPO
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 13
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/pdf/2510.11683
β’ PDF: https://arxiv.org/pdf/2510.11683
β’ Github: https://github.com/THU-KEG/BGPO
πΉ Datasets citing this paper:
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πΉ Title: SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12784
β’ PDF: https://arxiv.org/pdf/2510.12784
β’ Project Page: https://waynejin0918.github.io/srum_web/
β’ Github: https://github.com/WayneJin0918/SRUM
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12784
β’ PDF: https://arxiv.org/pdf/2510.12784
β’ Project Page: https://waynejin0918.github.io/srum_web/
β’ Github: https://github.com/WayneJin0918/SRUM
πΉ Datasets citing this paper:
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πΉ Title: Dr.LLM: Dynamic Layer Routing in LLMs
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12773
β’ PDF: https://arxiv.org/pdf/2510.12773
β’ Github: https://github.com/parameterlab/dr-llm
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12773
β’ PDF: https://arxiv.org/pdf/2510.12773
β’ Github: https://github.com/parameterlab/dr-llm
πΉ Datasets citing this paper:
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β€1
πΉ Title: Spatial Forcing: Implicit Spatial Representation Alignment for Vision-language-action Model
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: http://arxiv.org/abs/2510.12276
β’ PDF: https://arxiv.org/pdf/2510.12276
β’ Github: https://github.com/OpenHelix-Team/Spatial-Forcing
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: http://arxiv.org/abs/2510.12276
β’ PDF: https://arxiv.org/pdf/2510.12276
β’ Github: https://github.com/OpenHelix-Team/Spatial-Forcing
πΉ Datasets citing this paper:
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πΉ Title: What If : Understanding Motion Through Sparse Interactions
πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12777
β’ PDF: https://arxiv.org/pdf/2510.12777
β’ Project Page: https://compvis.github.io/flow-poke-transformer/
β’ Github: https://github.com/CompVis/flow-poke-transformer
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 14
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.12777
β’ PDF: https://arxiv.org/pdf/2510.12777
β’ Project Page: https://compvis.github.io/flow-poke-transformer/
β’ Github: https://github.com/CompVis/flow-poke-transformer
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