✨CADEvolve: Creating Realistic CAD via Program Evolution

📝 Summary:
CADEvolve presents an evolution-based pipeline using VLM-guided edits to generate complex CAD programs from simple primitives. It creates a large dataset of 1.3 million scripts, enabling fine-tuned VLMs to achieve state-of-the-art Image2CAD performance.

🔹 Publication Date: Published on Feb 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16317
• PDF: https://arxiv.org/pdf/2602.16317
• Github: https://github.com/zhemdi/CADEvolve

🔹 Models citing this paper:
• https://huggingface.co/kulibinai/cadevolve-rl1

✨ Datasets citing this paper:
• https://huggingface.co/datasets/kulibinai/cadevolve

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

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#CAD #ProgramEvolution #VLMs #Image2CAD #AI

✨Reinforced Fast Weights with Next-Sequence Prediction

📝 Summary:
REFINE is an RL framework that improves fast weight models for long-context tasks. It uses next-sequence prediction NSP instead of next-token prediction, enhancing long-range dependency capture. Experiments show it consistently outperforms supervised fine-tuning.

🔹 Publication Date: Published on Feb 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16704
• PDF: https://arxiv.org/pdf/2602.16704
• Github: https://github.com/princetonvisualai/ReFINE/

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#ReinforcementLearning #MachineLearning #DeepLearning #NLP #AI

✨Learning Personalized Agents from Human Feedback

📝 Summary:
PAHF enables AI agents to continually personalize through explicit user memory and dual feedback. It rapidly adapts to changing user preferences by integrating pre-action clarification and post-action updates, significantly reducing personalization error and improving learning speed.

🔹 Publication Date: Published on Feb 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16173
• PDF: https://arxiv.org/pdf/2602.16173
• Project Page: https://personalized-ai.github.io/
• Github: https://github.com/facebookresearch/PAHF

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

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#AI #Personalization #HumanAIInteraction #MachineLearning #AIAgents

✨OPBench: A Graph Benchmark to Combat the Opioid Crisis

📝 Summary:
OPBench is the first comprehensive graph benchmark to systematically evaluate graph learning methods for the opioid crisis. It includes five diverse datasets across three domains and a unified framework, providing insights for future research.

🔹 Publication Date: Published on Feb 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.14602
• PDF: https://arxiv.org/pdf/2602.14602
• Github: https://github.com/Tianyi-Billy-Ma/OPBench

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

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#OpioidCrisis #GraphLearning #DataScience #MachineLearning #PublicHealth

✨Unified Latents (UL): How to train your latents

📝 Summary:
Unified Latents UL learns joint latent representations using diffusion prior regularization and decoding. It achieves competitive FID of 1.4 on ImageNet-512 with fewer training FLOPs and sets a new state of the art FVD of 1.3 on Kinetics-600.

🔹 Publication Date: Published on Feb 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.17270
• PDF: https://arxiv.org/pdf/2602.17270

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

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#GenerativeAI #DiffusionModels #LatentSpace #ImageGeneration #VideoGeneration

✨Arcee Trinity Large Technical Report

📝 Summary:
Arcee Trinity introduces sparse Mixture-of-Experts models Nano, Mini, Large with up to 400B total parameters. They feature advanced attention, novel normalization, and sigmoid MoE routing, trained on massive token datasets.

🔹 Publication Date: Published on Feb 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.17004
• PDF: https://arxiv.org/pdf/2602.17004

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

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#MixtureOfExperts #LargeLanguageModels #SparseModels #DeepLearning #AI

✨TactAlign: Human-to-Robot Policy Transfer via Tactile Alignment

📝 Summary:
TactAlign transfers human tactile demonstrations to robots with different embodiments. It aligns human and robot tactile signals into a shared latent space without paired data, improving policy transfer for contact-rich tasks and enabling zero-shot transfer.

🔹 Publication Date: Published on Feb 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.13579
• PDF: https://arxiv.org/pdf/2602.13579
• Project Page: https://yswi.github.io/tactalign/

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

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#Robotics #TactileRobotics #PolicyTransfer #HRI #AI

✨Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report v1.5

📝 Summary:
This report assesses frontier AI risks, updating granular scenarios for cyber offense, manipulation, deception, uncontrolled AI R&D, and self-replication. It also proposes robust mitigation strategies for secure deployment of advanced AI systems.

🔹 Publication Date: Published on Feb 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.14457
• PDF: https://arxiv.org/pdf/2602.14457
• Project Page: https://ai45lab.github.io/safeworkf1-page/

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning

📝 Summary:
A trainable sparse attention method called SpargeAttention2 is proposed that achieves high sparsity in diffusion models while maintaining generation quality through hybrid masking rules and distillati...

🔹 Publication Date: Published on Feb 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.13515
• PDF: https://arxiv.org/pdf/2602.13515

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Mobile-Agent-v3.5: Multi-platform Fundamental GUI Agents

📝 Summary:
GUI-Owl-1.5 is a multi-platform GUI agent model with varying sizes that achieves superior performance across GUI automation, grounding, tool-calling, and memory tasks through innovations in data pipel...

🔹 Publication Date: Published on Feb 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16855
• PDF: https://arxiv.org/pdf/2602.16855
• Project Page: https://github.com/X-PLUG/MobileAgent/tree/main/Mobile-Agent-v3.5
• Github: https://github.com/X-PLUG/MobileAgent

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨DDiT: Dynamic Patch Scheduling for Efficient Diffusion Transformers

📝 Summary:
Dynamic tokenization improves diffusion transformer efficiency by adjusting patch sizes based on content complexity and denoising timestep, achieving significant speedup without quality loss. AI-gener...

🔹 Publication Date: Published on Feb 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16968
• PDF: https://arxiv.org/pdf/2602.16968

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Computer-Using World Model

📝 Summary:
A world model for desktop software that predicts UI state changes through textual description followed by visual synthesis, improving decision quality and execution robustness in computer-using tasks....

🔹 Publication Date: Published on Feb 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.17365
• PDF: https://arxiv.org/pdf/2602.17365

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨2Mamba2Furious: Linear in Complexity, Competitive in Accuracy

📝 Summary:
Researchers enhance linear attention by simplifying Mamba-2 and improving its architectural components to achieve near-softmax accuracy while maintaining memory efficiency for long sequences. AI-gener...

🔹 Publication Date: Published on Feb 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.17363
• PDF: https://arxiv.org/pdf/2602.17363
• Github: https://github.com/gmongaras/2Mamba2Furious

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Discovering Multiagent Learning Algorithms with Large Language Models

📝 Summary:
AlphaEvolve, an evolutionary coding agent using large language models, automatically discovers new multiagent learning algorithms for imperfect-information games by evolving regret minimization and po...

🔹 Publication Date: Published on Feb 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16928
• PDF: https://arxiv.org/pdf/2602.16928

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨PaperBench: Evaluating AI's Ability to Replicate AI Research

📝 Summary:
PaperBench evaluates AI agents' ability to replicate state-of-the-art AI research by decomposing replication tasks into graded sub-tasks, using both LLM-based and human judges to assess performance. A...

🔹 Publication Date: Published on Apr 2, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2504.01848
• PDF: https://arxiv.org/pdf/2504.01848
• Github: https://github.com/openai/preparedness

✨ Datasets citing this paper:
• https://huggingface.co/datasets/josancamon/paperbench
• https://huggingface.co/datasets/ai-coscientist/researcher-ablation-bench

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨References Improve LLM Alignment in Non-Verifiable Domains

📝 Summary:
References improve LLM alignment in non-verifiable domains. Reference-guided LLM-evaluators act as soft verifiers, boosting judge accuracy and enabling self-improvement for post-training. This method outperforms SFT and reference-free techniques, achieving strong results.

🔹 Publication Date: Published on Feb 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16802
• PDF: https://arxiv.org/pdf/2602.16802
• Github: https://github.com/yale-nlp/RLRR

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨FRAPPE: Infusing World Modeling into Generalist Policies via Multiple Future Representation Alignment

📝 Summary:
FRAPPE addresses limitations in world modeling for robotics by using parallel progressive expansion to improve representation alignment and reduce error accumulation in predictive models. AI-generated...

🔹 Publication Date: Published on Feb 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.17259
• PDF: https://arxiv.org/pdf/2602.17259
• Project Page: https://h-zhao1997.github.io/frappe/
• Github: https://github.com/OpenHelix-Team/frappe

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨"What Are You Doing?": Effects of Intermediate Feedback from Agentic LLM In-Car Assistants During Multi-Step Processing

📝 Summary:
Intermediate feedback from in-car AI assistants improves user experience, trust, and perceived speed, reducing task load. Users prefer adaptive feedback, starting transparently and becoming less verbose as reliability increases.

🔹 Publication Date: Published on Feb 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.15569
• PDF: https://arxiv.org/pdf/2602.15569
• Github: https://github.com/johanneskirmayr/agentic_llm_feedback

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

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#LLM #AI #HCI #AutomotiveAI #UserExperience

✨World Models for Policy Refinement in StarCraft II

📝 Summary:
StarWM is the first world model for StarCraft II predicting future observations under partial observability using a structured textual representation. It achieves significant offline prediction accuracy and, integrated into a decision system, yields substantial win-rate improvements against SC2s ...

🔹 Publication Date: Published on Feb 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.14857
• PDF: https://arxiv.org/pdf/2602.14857
• Github: https://github.com/yxzzhang/StarWM

🔹 Models citing this paper:
• https://huggingface.co/yxzhang2024/StarWM

✨ Datasets citing this paper:
• https://huggingface.co/datasets/yxzhang2024/SC2-Dynamics-50K

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

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#WorldModels #StarCraftII #AI #ReinforcementLearning #DeepLearning

✨ArXiv-to-Model: A Practical Study of Scientific LM Training

📝 Summary:
This paper details training a 1.36B scientific language model from raw arXiv LaTeX sources with limited computational resources. It reveals how preprocessing, tokenization, and infrastructure significantly impact training stability and data utilization. The work provides practical insights for re...

🔹 Publication Date: Published on Feb 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.17288
• PDF: https://arxiv.org/pdf/2602.17288
• Project Page: https://kitefishai.com
• Github: https://github.com/kitefishai/KiteFish-A1-1.5B-Math

🔹 Models citing this paper:
• https://huggingface.co/KiteFishAI/KiteFish-A1-1.5B-Math

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

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#LLM #ScientificAI #MLOps #ModelTraining #NLP

✨StereoAdapter-2: Globally Structure-Consistent Underwater Stereo Depth Estimation

📝 Summary:
StereoAdapter-2 improves underwater stereo depth estimation by replacing ConvGRU with a ConvSS2D operator for efficient, long-range disparity propagation. It also introduces UW-StereoDepth-80K, a new large-scale synthetic dataset. This approach achieves state-of-the-art zero-shot performance on u...

🔹 Publication Date: Published on Feb 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.16915
• PDF: https://arxiv.org/pdf/2602.16915
• Project Page: https://aigeeksgroup.github.io/StereoAdapter-2
• Github: https://aigeeksgroup.github.io/StereoAdapter-2

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

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#UnderwaterAI #ComputerVision #DeepLearning #StereoVision #Dataset