✨LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning

📝 Summary:
LatentChem enables chemical reasoning through continuous latent space computations instead of discrete textual tokens, achieving superior performance and efficiency compared to traditional chain-of-th...

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07075
• PDF: https://arxiv.org/pdf/2602.07075

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✨AgentCPM-Report: Interleaving Drafting and Deepening for Open-Ended Deep Research

📝 Summary:
AgentCPM-Report presents a lightweight local solution for deep research report generation using a Writing As Reasoning Policy framework and multi-stage agentic training to enhance small models' reason...

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.06540
• PDF: https://arxiv.org/pdf/2602.06540
• Github: https://github.com/OpenBMB/AgentCPM

🔹 Models citing this paper:
• https://huggingface.co/openbmb/AgentCPM-Report
• https://huggingface.co/openbmb/AgentCPM-Report-GGUF

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✨When and How Much to Imagine: Adaptive Test-Time Scaling with World Models for Visual Spatial Reasoning

📝 Summary:
Adaptive test-time framework with world models enables selective visual imagination for spatial reasoning, improving efficiency and reliability by determining when imagination is necessary. AI-generat...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08236
• PDF: https://arxiv.org/pdf/2602.08236
• Project Page: https://adaptive-visual-tts.github.io/
• Github: https://adaptive-visual-tts.github.io/

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✨Recurrent-Depth VLA: Implicit Test-Time Compute Scaling of Vision-Language-Action Models via Latent Iterative Reasoning

📝 Summary:
RD-VLA introduces a recurrent architecture for VLA models, using latent iterative refinement for adaptive compute. It maintains constant memory, boosts success on complex tasks, and offers significant speedups.

🔹 Publication Date: Published on Feb 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07845
• PDF: https://arxiv.org/pdf/2602.07845
• Project Page: https://rd-vla.github.io/
• Github: https://github.com/rd-vla/rd-vla

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✨Demo-ICL: In-Context Learning for Procedural Video Knowledge Acquisition

📝 Summary:
Researchers introduce a new video understanding task and benchmark that evaluates models' ability to learn from few-shot demonstrations, along with a specialized MLLM architecture trained using a two-...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08439
• PDF: https://arxiv.org/pdf/2602.08439
• Github: https://github.com/dongyh20/Demo-ICL

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

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✨QuantaAlpha: An Evolutionary Framework for LLM-Driven Alpha Mining

📝 Summary:
Financial markets are noisy and non-stationary, making alpha mining highly sensitive to noise in backtesting results and sudden market regime shifts. While recent agentic frameworks improve alpha mini...

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07085
• PDF: https://arxiv.org/pdf/2602.07085
• Github: https://github.com/QuantaAlpha/QuantaAlpha

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✨LLaDA2.1: Speeding Up Text Diffusion via Token Editing

📝 Summary:
LLaDA2.1 introduces a novel token-to-token editing approach with speed and quality modes, enhanced through reinforcement learning for improved reasoning and instruction following in large language dif...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08676
• PDF: https://arxiv.org/pdf/2602.08676
• Github: https://github.com/inclusionAI/LLaDA2.X

🔹 Models citing this paper:
• https://huggingface.co/inclusionAI/LLaDA2.1-mini
• https://huggingface.co/inclusionAI/LLaDA2.1-flash

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

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✨WorldCompass: Reinforcement Learning for Long-Horizon World Models

📝 Summary:
WorldCompass enhances long-horizon video-based world models through reinforcement learning post-training with clip-level rollouts, complementary rewards, and efficient RL algorithms. AI-generated summ...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09022
• PDF: https://arxiv.org/pdf/2602.09022
• Project Page: https://3d-models.hunyuan.tencent.com/world/

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✨WildReward: Learning Reward Models from In-the-Wild Human Interactions

📝 Summary:
WildReward demonstrates that reward models can be effectively trained from in-the-wild user interactions using ordinal regression, achieving performance comparable to traditional methods while benefit...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08829
• PDF: https://arxiv.org/pdf/2602.08829

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

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✨Reliable and Responsible Foundation Models: A Comprehensive Survey

📝 Summary:
Foundation models including LLMs, MLLMs, and generative models require reliable and responsible development addressing bias, security, explainability, and other critical issues for trustworthy deploym...

🔹 Publication Date: Published on Feb 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08145
• PDF: https://arxiv.org/pdf/2602.08145

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

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✨MOVA: Towards Scalable and Synchronized Video-Audio Generation

📝 Summary:
MOVA is an open-source model generating synchronized video-audio content, including lip-synced speech and sound effects. It employs a 32B-parameter Mixture-of-Experts architecture for image-text to video-audio generation, overcoming limitations of previous cascaded and closed-source systems.

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08794
• PDF: https://arxiv.org/pdf/2602.08794
• Project Page: https://mosi.cn/models/mova
• Github: https://github.com/OpenMOSS/MOVA

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✨InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery

📝 Summary:
InternAgent-1.5 is a unified system for autonomous scientific discovery that integrates computational modeling and experimental research through coordinated subsystems for generation, verification, an...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08990
• PDF: https://arxiv.org/pdf/2602.08990

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

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✨How2Everything: Mining the Web for How-To Procedures to Evaluate and Improve LLMs

📝 Summary:
A scalable framework for evaluating and improving goal-conditioned procedure generation using large-scale web mining, automated scoring, and reinforcement learning to enhance step-by-step instruction ...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08808
• PDF: https://arxiv.org/pdf/2602.08808
• Github: https://github.com/lilakk/how2everything

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✨GISA: A Benchmark for General Information-Seeking Assistant

📝 Summary:
A new benchmark called GISA is introduced for evaluating information-seeking assistants, featuring human-crafted queries with structured answer formats and live updates to prevent memorization. AI-gen...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08543
• PDF: https://arxiv.org/pdf/2602.08543

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

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✨Rolling Sink: Bridging Limited-Horizon Training and Open-Ended Testing in Autoregressive Video Diffusion

📝 Summary:
Autoregressive video diffusion models suffer from train-test gaps when generating long videos, but a training-free approach called Rolling Sink addresses this by maintaining AR cache and enabling ultr...

🔹 Publication Date: Published on Feb 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07775
• PDF: https://arxiv.org/pdf/2602.07775
• Project Page: https://rolling-sink.github.io/

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✨Concept-Aware Privacy Mechanisms for Defending Embedding Inversion Attacks

📝 Summary:
SPARSE is a user-centric framework that protects text embeddings from privacy leaks by selectively perturbing sensitive dimensions using differentiable masking and Mahalanobis noise calibration. AI-ge...

🔹 Publication Date: Published on Feb 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07090
• PDF: https://arxiv.org/pdf/2602.07090

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

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✨Aster: Autonomous Scientific Discovery over 20x Faster Than Existing Methods

📝 Summary:
Aster is an AI agent that accelerates scientific discovery by iteratively improving programs, achieving state-of-the-art results across multiple domains including mathematics, biology, and machine lea...

🔹 Publication Date: Published on Feb 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07040
• PDF: https://arxiv.org/pdf/2602.07040
• Project Page: https://www.asterlab.ai/

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✨Weak-Driven Learning: How Weak Agents make Strong Agents Stronger

📝 Summary:
WMSS is a post-training paradigm that uses weak model checkpoints to identify and fill learning gaps, enabling continued improvement beyond conventional saturation points in large language models. AI-...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08222
• PDF: https://arxiv.org/pdf/2602.08222

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

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✨Theory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?

📝 Summary:
Current multimodal foundation models show limitations in maintaining coherent spatial beliefs during active exploration, exhibiting gaps between active and passive performance, inefficient exploration...

🔹 Publication Date: Published on Feb 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07055
• PDF: https://arxiv.org/pdf/2602.07055
• Project Page: https://theory-of-space.github.io/
• Github: https://github.com/mll-lab-nu/Theory-of-Space

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✨Learning-guided Kansa collocation for forward and inverse PDEs beyond linearity

📝 Summary:
Research explores PDE solvers including neural frameworks for scientific simulations, examining forward solutions, inverse problems, and equation discovery across multi-variable and non-linear systems...

🔹 Publication Date: Published on Feb 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07970
• PDF: https://arxiv.org/pdf/2602.07970

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✨MotionCrafter: Dense Geometry and Motion Reconstruction with a 4D VAE

📝 Summary:
MotionCrafter is a video diffusion framework that jointly reconstructs 4D geometry and estimates dense motion using a novel joint representation and 4D VAE architecture. AI-generated summary We introd...

🔹 Publication Date: Published on Feb 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08961
• PDF: https://arxiv.org/pdf/2602.08961
• Project Page: https://ruijiezhu94.github.io/MotionCrafter_Page
• Github: https://github.com/TencentARC/MotionCrafter

🔹 Models citing this paper:
• https://huggingface.co/TencentARC/MotionCrafter

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