✨FrameDiffuser: G-Buffer-Conditioned Diffusion for Neural Forward Frame Rendering

📝 Summary:
FrameDiffuser is an autoregressive neural rendering framework. It generates temporally consistent, photorealistic frames using G-buffer data and its own previous output. This achieves interactive speed and high quality compared to prior methods.

🔹 Publication Date: Published on Dec 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16670
• PDF: https://arxiv.org/pdf/2512.16670

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#NeuralRendering #DiffusionModels #ComputerGraphics #RealtimeRendering #DeepLearning

✨JustRL: Scaling a 1.5B LLM with a Simple RL Recipe

📝 Summary:
JustRL uses a minimal single-stage RL approach with fixed hyperparameters to achieve state-of-the-art performance on 1.5B reasoning models. It uses less compute and shows stable training, suggesting that complex RL methods for LLMs may be unnecessary and can even hinder exploration.

🔹 Publication Date: Published on Dec 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16649
• PDF: https://arxiv.org/pdf/2512.16649

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#ReinforcementLearning #LLMs #DeepLearning #AIResearch #ModelScaling

✨Vision-Language-Action Models for Autonomous Driving: Past, Present, and Future

📝 Summary:
Vision-Language-Action VLA models integrate visual, linguistic, and action capabilities for autonomous driving. They aim for interpretable and human-aligned policies, addressing prior system limitations. This paper characterizes VLA paradigms, datasets, and future challenges.

🔹 Publication Date: Published on Dec 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16760
• PDF: https://arxiv.org/pdf/2512.16760
• Project Page: https://worldbench.github.io/vla4ad
• Github: https://github.com/worldbench/awesome-vla-for-ad

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#VLAModels #AutonomousDriving #AI #DeepLearning #Robotics

✨Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMs

📝 Summary:
This paper benchmarks SpeechLLMs against cascaded systems for speech-to-text translation. It finds cascaded systems are more reliable overall, while SpeechLLMs match them only in select cases. Integrating an LLM is essential for high quality speech translation.

🔹 Publication Date: Published on Dec 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16378
• PDF: https://arxiv.org/pdf/2512.16378
• Github: https://github.com/sarapapi/hearing2translate

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#SpeechTranslation #LLMs #NLP #AIResearch #DeepLearning

✨EasyV2V: A High-quality Instruction-based Video Editing Framework

📝 Summary:
EasyV2V is a framework for instruction-based video editing that combines diverse data sources, leverages pretrained text-to-video models with LoRA fine-tuning, and uses unified spatiotemporal control. This innovative approach achieves state-of-the-art results in video editing.

🔹 Publication Date: Published on Dec 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16920
• PDF: https://arxiv.org/pdf/2512.16920
• Github: https://snap-research.github.io/easyv2v/

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#VideoEditing #AI #DeepLearning #ComputerVision #TextToVideo

✨Bidirectional Normalizing Flow: From Data to Noise and Back

📝 Summary:
Bidirectional Normalizing Flow BiFlow improves generative modeling by learning an approximate noise-to-data inverse, removing the need for exact invertibility. This allows flexible architectures, yielding better generation quality and accelerating sampling by up to two orders of magnitude.

🔹 Publication Date: Published on Dec 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10953
• PDF: https://arxiv.org/pdf/2512.10953

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#NormalizingFlows #GenerativeAI #MachineLearning #DeepLearning #DataScience

✨Nemotron-Math: Efficient Long-Context Distillation of Mathematical Reasoning from Multi-Mode Supervision

📝 Summary:
Nemotron-Math is a new large mathematical reasoning dataset with diverse styles and Python tool integration, generated from gpt-oss-120b. It combines competition problems with real-world queries, achieving state-of-the-art performance and accelerating long-context training.

🔹 Publication Date: Published on Dec 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.15489
• PDF: https://arxiv.org/pdf/2512.15489

✨ Datasets citing this paper:
• https://huggingface.co/datasets/nvidia/Nemotron-Math-v2
• https://huggingface.co/datasets/nvidia/Nemotron-Math-Proofs-v1

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#NemotronMath #MathematicalReasoning #LargeLanguageModels #AIDataset #DeepLearning

✨MomaGraph: State-Aware Unified Scene Graphs with Vision-Language Model for Embodied Task Planning

📝 Summary:
MomaGraph-R1, a vision-language model trained with reinforcement learning, achieves state-of-the-art performance in predicting task-oriented scene graphs and zero-shot task planning in household envir...

🔹 Publication Date: Published on Dec 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16909
• PDF: https://arxiv.org/pdf/2512.16909
• Github: https://hybridrobotics.github.io/MomaGraph/

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#VisionLanguageModel #EmbodiedAI #ReinforcementLearning #SceneGraphs #Robotics

✨Sharing State Between Prompts and Programs

📝 Summary:
Nightjar programming system introduces shared program state abstraction to facilitate interoperability between natural language code and Python, enhancing task accuracy and reducing code size. AI-gene...

🔹 Publication Date: Published on Dec 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.14805
• PDF: https://arxiv.org/pdf/2512.14805
• Github: https://github.com/psg-mit/nightjarpy/

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨ModelTables: A Corpus of Tables about Models

📝 Summary:
ModelTables is a new benchmark corpus of 90K structured performance and configuration tables about AI models, linking them to their context. Its evaluation for table search reveals a clear need for improved methods in understanding structured model knowledge.

🔹 Publication Date: Published on Dec 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16106
• PDF: https://arxiv.org/pdf/2512.16106
• Github: https://github.com/RJMillerLab/ModelTables

==================================

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#AI #Datasets #MachineLearning #StructuredData #TableSearch

✨Improving Recursive Transformers with Mixture of LoRAs

📝 Summary:
This paper proposes Mixture of LoRAs MoL to restore expressivity in parameter-shared recursive transformers. MoL uses token-conditional weight modulation in a shared feed-forward network, achieving state-of-the-art performance with compact models. An expert-merging procedure further enables effic...

🔹 Publication Date: Published on Dec 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12880
• PDF: https://arxiv.org/pdf/2512.12880

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Reasoning Within the Mind: Dynamic Multimodal Interleaving in Latent Space

📝 Summary:
DMLR is a new framework inspired by human cognition, dynamically interleaving reasoning and perception in latent space. It uses confidence-guided optimization for latent think tokens and injects relevant visual features, improving cross-modal reasoning and perception efficiently.

🔹 Publication Date: Published on Dec 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12623
• PDF: https://arxiv.org/pdf/2512.12623
• Project Page: https://mllm-dmlr.github.io/
• Github: https://mllm-dmlr.github.io

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#AI #DataScience #MachineLearning #HuggingFace #Research

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