✨The Trinity of Consistency as a Defining Principle for General World Models

📝 Summary:
This paper proposes the Trinity of Consistency modal, spatial, temporal as a foundational theoretical framework for General World Models. It systematically reviews multimodal learning through this lens and introduces CoW-Bench, a new benchmark for evaluating current and future models.

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23152
• PDF: https://arxiv.org/pdf/2602.23152
• Project Page: https://openraiser.github.io/CoW-Bench/
• Github: https://github.com/openraiser/awesome-world-model-evolution

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✨OmniGAIA: Towards Native Omni-Modal AI Agents

📝 Summary:
OmniGAIA benchmark evaluates multi-modal agents on complex reasoning tasks across video, audio, and image modalities, while OmniAtlas agent improves tool-use capabilities through hindsight-guided tree...

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.22897
• PDF: https://arxiv.org/pdf/2602.22897
• Github: https://github.com/RUC-NLPIR/OmniGAIA

✨ Datasets citing this paper:
• https://huggingface.co/datasets/RUC-NLPIR/OmniGAIA
• https://huggingface.co/datasets/RUC-NLPIR/Omnimodal-Agent-SFT-2K

✨ Spaces citing this paper:
• https://huggingface.co/spaces/RUC-NLPIR/OmniGAIA-Leaderboard

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✨Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving

📝 Summary:
A risk-aware framework for autonomous driving that uses world modeling and risk evaluation to generalize beyond expert demonstrations without requiring explicit expert supervision. AI-generated summar...

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23259
• PDF: https://arxiv.org/pdf/2602.23259

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✨DyaDiT: A Multi-Modal Diffusion Transformer for Socially Favorable Dyadic Gesture Generation

📝 Summary:
DyaDiT is a multi-modal diffusion transformer that generates contextually appropriate human motion from dyadic audio signals by capturing interaction dynamics between two speakers. AI-generated summar...

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23165
• PDF: https://arxiv.org/pdf/2602.23165

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✨GeoWorld: Geometric World Models

📝 Summary:
GeoWorld addresses limitations in energy-based predictive world models by utilizing hyperbolic geometry to preserve latent state structures and improve long-horizon prediction performance. AI-generate...

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23058
• PDF: https://arxiv.org/pdf/2602.23058
• Project Page: https://steve-zeyu-zhang.github.io/GeoWorld

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✨veScale-FSDP: Flexible and High-Performance FSDP at Scale

📝 Summary:
veScale-FSDP introduces a redesigned fully sharded data parallel system with flexible sharding and structure-aware planning to improve scalability and efficiency for large-scale model training. AI-gen...

🔹 Publication Date: Published on Feb 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.22437
• PDF: https://arxiv.org/pdf/2602.22437
• Github: https://github.com/volcengine/veScale

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✨Imagination Helps Visual Reasoning, But Not Yet in Latent Space

📝 Summary:
Research reveals that latent visual reasoning in multimodal models suffers from input-latent and latent-answer disconnects, leading to the proposal of CapImagine, a text-based approach that outperform...

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.22766
• PDF: https://arxiv.org/pdf/2602.22766
• Github: https://github.com/Michael4933/CapImagine

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✨Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization

📝 Summary:
EMPO² is a hybrid reinforcement learning framework that enhances exploration for large language model agents by integrating memory mechanisms with on- and off-policy updates, demonstrating improved pe...

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23008
• PDF: https://arxiv.org/pdf/2602.23008

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✨Causal Motion Diffusion Models for Autoregressive Motion Generation

📝 Summary:
Causal Motion Diffusion Models introduce a unified framework for autoregressive motion generation using a causal diffusion transformer in a semantically aligned latent space, enabling fast, high-quali...

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.22594
• PDF: https://arxiv.org/pdf/2602.22594
• Project Page: https://yu1ut.com/CMDM-HP/

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✨Efficient Continual Learning in Language Models via Thalamically Routed Cortical Columns

📝 Summary:
TRC2 introduces a sparse, chunk-parallel architecture for language models to address continual learning challenges. It enables rapid adaptation and prevents catastrophic forgetting, improving the stability-plasticity tradeoff with efficient compute.

🔹 Publication Date: Published on Feb 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.22479
• PDF: https://arxiv.org/pdf/2602.22479
• Project Page: https://trc2lm.github.io

🔹 Models citing this paper:
• https://huggingface.co/akhadangi/trc2

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