🔹 Title: VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing

🔹 Publication Date: Published on Oct 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05213
• PDF: https://arxiv.org/pdf/2510.05213
• Project Page: https://yixiaowang7.github.io/ver_page/

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🔹 Title: HUME: Measuring the Human-Model Performance Gap in Text Embedding Task

🔹 Publication Date: Published on Oct 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10062
• PDF: https://arxiv.org/pdf/2510.10062

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🔹 Title: Spotlight on Token Perception for Multimodal Reinforcement Learning

🔹 Publication Date: Published on Oct 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.09285
• PDF: https://arxiv.org/pdf/2510.09285
• Project Page: https://huggingface.co/collections/chamber111/vppo-data-68e7aaafe1bffbab844d341b
• Github: https://github.com/huaixuheqing/VPPO-RL

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/chamber111/VPPO-Eval
• https://huggingface.co/datasets/chamber111/VPPO_ViRL39K_train
• https://huggingface.co/datasets/chamber111/VPPO_MMK12_validation

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🔹 Title: ACADREASON: Exploring the Limits of Reasoning Models with Academic Research Problems

🔹 Publication Date: Published on Oct 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.11652
• PDF: https://arxiv.org/pdf/2510.11652

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🔹 Title: InternSVG: Towards Unified SVG Tasks with Multimodal Large Language Models

🔹 Publication Date: Published on Oct 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.11341
• PDF: https://arxiv.org/pdf/2510.11341
• Project Page: https://hmwang2002.github.io/release/internsvg/
• Github: https://github.com/hmwang2002/InternSVG

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🔹 Title: From Data to Rewards: a Bilevel Optimization Perspective on Maximum Likelihood Estimation

🔹 Publication Date: Published on Oct 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07624
• PDF: https://arxiv.org/pdf/2510.07624
• Github: https://github.com/abenechehab/nll_to_po

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🔹 Title: Latent Refinement Decoding: Enhancing Diffusion-Based Language Models by Refining Belief States

🔹 Publication Date: Published on Oct 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.11052
• PDF: https://arxiv.org/pdf/2510.11052

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🔹 Title: CoBia: Constructed Conversations Can Trigger Otherwise Concealed Societal Biases in LLMs

🔹 Publication Date: Published on Oct 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.09871
• PDF: https://arxiv.org/pdf/2510.09871
• Project Page: https://github.com/nafisenik/CoBia
• Github: https://github.com/nafisenik/CoBia

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🔹 Title: Through the Perspective of LiDAR: A Feature-Enriched and Uncertainty-Aware Annotation Pipeline for Terrestrial Point Cloud Segmentation

🔹 Publication Date: Published on Oct 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06582
• PDF: https://arxiv.org/pdf/2510.06582
• Project Page: https://fz-rit.github.io/through-the-lidars-eye/

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🔹 Title: The Curious Case of Factual (Mis)Alignment between LLMs' Short- and Long-Form Answers

🔹 Publication Date: Published on Oct 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.11218
• PDF: https://arxiv.org/pdf/2510.11218
• Github: https://github.com/WorldHellow/SLAQ

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🔹 Title: ViSurf: Visual Supervised-and-Reinforcement Fine-Tuning for Large Vision-and-Language Models

🔹 Publication Date: Published on Oct 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2510.10606
• PDF: https://arxiv.org/pdf/2510.10606
• Github: https://github.com/dvlab-research/ViSurf?tab=readme-ov-file

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🔹 Title: SwarmSys: Decentralized Swarm-Inspired Agents for Scalable and Adaptive Reasoning

🔹 Publication Date: Published on Oct 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10047
• PDF: https://arxiv.org/pdf/2510.10047

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🔹 Title: World-To-Image: Grounding Text-to-Image Generation with Agent-Driven World Knowledge

🔹 Publication Date: Published on Oct 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.04201
• PDF: https://arxiv.org/pdf/2510.04201
• Github: https://github.com/mhson-kyle/World-To-Image

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🔹 Title: AndesVL Technical Report: An Efficient Mobile-side Multimodal Large Language Model

🔹 Publication Date: Published on Oct 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.11496
• PDF: https://arxiv.org/pdf/2510.11496

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🔹 Title: A Tale of LLMs and Induced Small Proxies: Scalable Agents for Knowledge Mining

🔹 Publication Date: Published on Oct 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.01427
• PDF: https://arxiv.org/pdf/2510.01427
• Github: https://github.com/LongfeiYun17/falconer

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🔹 Title: Multimodal Policy Internalization for Conversational Agents

🔹 Publication Date: Published on Oct 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.09474
• PDF: https://arxiv.org/pdf/2510.09474
• Project Page: https://mikewangwzhl.github.io/TriMPI/
• Github: https://mikewangwzhl.github.io/TriMPI/

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🔹 Title: The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections

🔹 Publication Date: Published on Oct 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.09023
• PDF: https://arxiv.org/pdf/2510.09023

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🔹 Title: MultiCOIN: Multi-Modal COntrollable Video INbetweening

🔹 Publication Date: Published on Oct 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.08561
• PDF: https://arxiv.org/pdf/2510.08561

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🔹 Title: oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning

🔹 Publication Date: Published on Oct 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07731
• PDF: https://arxiv.org/pdf/2510.07731
• Github: https://github.com/skylarkie/oMeBench

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🔹 Title: VLM-Guided Adaptive Negative Prompting for Creative Generation

🔹 Publication Date: Published on Oct 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.10715
• PDF: https://arxiv.org/pdf/2510.10715
• Github: https://shelley-golan.github.io/VLM-Guided-Creative-Generation/

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🤖🧠 Thinking with Camera 2.0: A Powerful Multimodal Model for Camera-Centric Understanding and Generation

🗓️ 14 Oct 2025
📚 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 “a cat on a sofa” “a red car on the road” but struggle to reason about how the image was captured: the camera’s ...

#MultimodalAI #CameraCentricUnderstanding #VisionLanguageModels #AIResearch #ComputerVision #GenerativeModels