✨VerseCrafter: Dynamic Realistic Video World Model with 4D Geometric Control

📝 Summary:
VerseCrafter is a 4D-aware video world model that enables unified control over camera and object dynamics through 4D geometric control representation and video diffusion models. AI-generated summary V...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05138
• PDF: https://arxiv.org/pdf/2601.05138

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✨Agent-as-a-Judge

📝 Summary:
Large language models face limitations in evaluating complex, multi-step tasks, prompting the development of agent-based evaluation systems that utilize planning, tool-augmented verification, and mult...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05111
• PDF: https://arxiv.org/pdf/2601.05111

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✨DiffCoT: Diffusion-styled Chain-of-Thought Reasoning in LLMs

📝 Summary:
DiffCoT reformulates chain-of-thought reasoning as an iterative denoising process using diffusion principles, enabling unified generation and correction of intermediate steps while maintaining causal ...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03559
• PDF: https://arxiv.org/pdf/2601.03559

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✨The Illusion of Specialization: Unveiling the Domain-Invariant "Standing Committee" in Mixture-of-Experts Models

📝 Summary:
Research challenges the assumption of domain specialization in Mixture of Experts models by identifying a persistent central committee of experts that dominates routing behavior across different domai...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03425
• PDF: https://arxiv.org/pdf/2601.03425

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✨GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization

📝 Summary:
Multi-reward RL with GRPO suffers from reward normalization collapse, leading to suboptimal training. GDPO solves this by decoupling individual reward normalization, preserving their relative differences for improved stability and optimization. GDPO consistently outperforms GRPO across various re...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05242
• PDF: https://arxiv.org/pdf/2601.05242
• Project Page: https://nvlabs.github.io/GDPO/
• Github: https://github.com/NVlabs/GDPO

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✨Plenoptic Video Generation

📝 Summary:
PlenopticDreamer enables consistent multi-view video re-rendering through synchronized generative hallucinations, leveraging camera-guided retrieval and progressive training mechanisms for improved te...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05239
• PDF: https://arxiv.org/pdf/2601.05239
• Project Page: https://research.nvidia.com/labs/dir/plenopticdreamer/

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✨DocDancer: Towards Agentic Document-Grounded Information Seeking

📝 Summary:
DocDancer is an end-to-end trained open-source document question answering agent that formulates the task as an information-seeking problem and uses a tool-driven framework with exploration and synthe...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05163
• PDF: https://arxiv.org/pdf/2601.05163

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✨Token-Level LLM Collaboration via FusionRoute

📝 Summary:
FusionRoute is a token-level multi-LLM collaboration framework that uses a lightweight router to select optimal experts and add complementary logits, outperforming existing methods in diverse tasks wh...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05106
• PDF: https://arxiv.org/pdf/2601.05106

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✨Safety at One Shot: Patching Fine-Tuned LLMs with A Single Instance

📝 Summary:
Safety alignment of large language models can be fully recovered with a single safety example, maintaining utility and achieving convergence in few epochs through identified low-rank gradient structur...

🔹 Publication Date: Published on Jan 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01887
• PDF: https://arxiv.org/pdf/2601.01887

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✨Memorization in 3D Shape Generation: An Empirical Study

📝 Summary:
Researchers develop a framework to measure memorization in 3D generative models and identify factors affecting it, finding that data modality and model design parameters influence how much training da...

🔹 Publication Date: Published on Dec 29, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.23628
• PDF: https://arxiv.org/pdf/2512.23628
• Github: https://github.com/zlab-princeton/3d-gen-mem

🔹 Models citing this paper:
• https://huggingface.co/pudashi/3DGenMem

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