با عرض سلام ما برای یکی از مقالاتمون در حوزه ی پزشکی نیاز به نفر ۴ ام داریم با قبولی شرایط پرداخت میتونیم اضافه کنیم.

@Raminmousa

📑 Machine learning-based drug-drug interaction prediction: a critical review of models, limitations, and data challenges


📎 Study the paper


@Machine_learn

با عرض سلام این مورد باقی مونده و این هفته سابمیت مقاله می باشد.
@Raminmousa

The Data Engineering Handbook

📚 Github

@Machine_learn

Crystal Generation with Space Group Informed Transformer

🖥 Github: https://github.com/deepmodeling/crystalformer

📕 Paper: https://arxiv.org/abs/2504.02367v1

🔗 Dataset: https://paperswithcode.com/dataset/alex-20

@Machine_learn

🔹 Title: Scalable Multi-Task Reinforcement Learning for Generalizable Spatial Intelligence in Visuomotor Agents


🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2507.23698

• PDF: https://arxiv.org/pdf/2507.23698

• Github: https://github.com/CraftJarvis/ROCKET-3

@Machine_learn

با عرض سلام ما برای یکی از مقالاتمون در حوزه ی پزشکی نیاز به نفر ۴ ام داریم با قبولی شرایط پرداخت میتونیم اضافه کنیم.

@Raminmousa

🔹 Title: Visual-CoG: Stage-Aware Reinforcement Learning with Chain of Guidance for Text-to-Image Generation

🔹 Publication Date: Published on Aug 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2508.18032
• PDF: https://arxiv.org/pdf/2508.18032

@Machine_learn

ComputerRL: Scaling End-to-End Online Reinforcement Learning for Computer Use Agents

📚 Read


@Machine_learn

Attacking LLMs and AI Agents: Advertisement Embedding Attacks Against LLMs

📚 Paper

@Machine_learn

📃 Energy-Based Transformers are Scalable Learners and Thinkers

Inference-time computation techniques, analogous to human System 2 Thinking, have recently become popular for improving model performances. In this paper, we ask the question "Is it possible to generalize these System 2 Thinking approaches, and develop models that learn to think solely from unsupervised learning?" Interestingly, we find the answer is yes, by learning to explicitly verify the compatibility between inputs and candidate-predictions, and then re-framing prediction problems as optimization with respect to this verifier. Specifically, we train Energy-Based Transformers (EBTs) -- a new class of Energy-Based Models (EBMs) -- to assign an energy value to every input and candidate-prediction pair, enabling predictions through gradient descent-based energy minimization until convergence. Across both discrete (text) and continuous (visual) modalities, we find EBTs scale faster than the dominant Transformer++ approach during training, achieving an up to 35% higher scaling rate with respect to data, batch size, parameters, FLOPs, and depth. During inference, EBTs improve performance with System 2 Thinking by 29% more than the Transformer++ on language tasks, and EBTs outperform Diffusion Transformers on image denoising while using fewer forward passes.

@Machine_learn

"Transcendence" is when an LLM, trained on diverse data from many experts, can exceed the ability of the individuals in its training data.

This paper demonstrates three types: when AI picks the right expert skill to use, when AI has less bias than experts & when it generalizes.

📚 Read

@Machine_learn

با عرض سلام ما برای یکی از مقالاتمون در حوزه ی پزشکی نیاز به نفر ۴ ام داریم با قبولی شرایط پرداخت میتونیم اضافه کنیم.

@Raminmousa

Scientific Visualization: Python + Matplotlib

📚 Book


@Machine_learn

"GPT-5 moves from human-comparable to above human-expert performance"

GPT-5 outperforms licensed human experts by 25-30% and achieves SOTA results on the US medical licensing exam and the MedQA benchmark.

I sound like a broken record, but AI models are better than most doctors.

📚 Paper

@Machine_learn

سلام
ما گروهی از دانشجویان اروپا و امریکا هستیم. ریسرچ ما در حال سابمیت دو‌ پیپر در زمینه کامپیوتر ساینس با موضوعات زیر در ژورنال‌های کامپیوتری هست :

- Customized Attention-based Model for Medical Image Classification.

- Robust and Efficient Model Training for on the Edge Devices .

برای هر کدام از پیپرها دو پوزیشن نویسنده خالی هست. در صورت تمایل لطفا به آی دی زیر پیام بدین:
@rezaa_alvandi

لطفا توجه بفرمایید که زمان سابمیت هر دو مقاله جمعه ۵ سپتامبر است.