Фильтр публикаций


Demystifying Long Chain-of-Thought Reasoning in LLMs

🖥 paper
🧠 code


@Machine_learn


CoSTI: Consistency Models for (a faster) Spatio-Temporal Imputation

31 Jan 2025 · Javier Solís-García, Belén Vega-Márquez, Juan A. Nepomuceno, Isabel A. Nepomuceno-Chamorro ·

Multivariate Time Series Imputation (MTSI) is crucial for many applications, such as healthcare monitoring and traffic management, where incomplete data can compromise decision-making. Existing state-of-the-art methods, like Denoising Diffusion Probabilistic Models (DDPMs), achieve high imputation accuracy; however, they suffer from significant computational costs and are notably time-consuming due to their iterative nature. In this work, we propose CoSTI, an innovative adaptation of Consistency Models (CMs) for the MTSI domain. CoSTI employs Consistency Training to achieve comparable imputation quality to DDPMs while drastically reducing inference times, making it more suitable for real-time applications. We evaluate CoSTI across multiple datasets and missing data scenarios, demonstrating up to a 98% reduction in imputation time with performance on par with diffusion-based models. This work bridges the gap between efficiency and accuracy in generative imputation tasks, providing a scalable solution for handling missing data in critical spatio-temporal systems.

Paper: https://arxiv.org/pdf/2501.19364v1.pdf

Code: https://github.com/javiersgjavi/costi



@Machine_learn


Репост из: Github LLMs
Awesome-LLM-as-a-judge Survey

Github

🔸https://t.me/deep_learning_proj


نفر ۵ از این پروژه همچنان خالی هست...!
@Raminmousa


RIGNO: A Graph-based framework for robust and accurate operator learning for PDEs on arbitrary domains


Paper: https://arxiv.org/pdf/2501.19205v1.pdf

Code: https://github.com/camlab-ethz/rigno



@Machine_learn


Free Certification Courses to Learn Data Analytics in 2025:

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@Machine_learn


A Little Bit of Reinforcement Learning
from Human Feedback

📓 Book


@Machine_learn


Репост из: Github LLMs
LLMs can see and hear without any training

30 Jan 2025 · Kumar Ashutosh, Yossi Gandelsman, Xinlei Chen, Ishan Misra, Rohit Girdhar ·

We present MILS: Multimodal Iterative LLM Solver, a surprisingly simple, training-free approach, to imbue multimodal capabilities into your favorite LLM. Leveraging their innate ability to perform multi-step reasoning, MILS prompts the LLM to generate candidate outputs, each of which are scored and fed back iteratively, eventually generating a solution to the task. This enables various applications that typically require training specialized models on task-specific data. In particular, we establish a new state-of-the-art on emergent zero-shot image, video and audio captioning. MILS seamlessly applies to media generation as well, discovering prompt rewrites to improve text-to-image generation, and even edit prompts for style transfer! Finally, being a gradient-free optimization approach, MILS can invert multimodal embeddings into text, enabling applications like cross-modal arithmetic.

Paper: https://arxiv.org/pdf/2501.18096v1.pdf

Code: https://github.com/facebookresearch/mils

https://t.me/deep_learning_proj


20% از کارهای این مقاله انجام شده و این اخرین فرصت برای جوین شدن به پروژست.

@Raminmousa




Репост из: Papers
با عرض سلام نفر ٥ ام از پروژه جديدمون باقي مونده و ٦ جايگاه ديگه پر شدن.
امكان اموزش كامل كار
كدنويسي كار
نحوه جمع اوري داده ها
نگارش مقاله در اين كار وجود داره


Project Title:
MedRec: Medical recommender system for image classification without retraining

Github: https://github.com/Ramin1Mousa/MedicalRec

Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence

Impact factor: 20.8




🔺 5- 300$
جهت مشارکت می تونید به ایدی بنده پیام بدین.
@Raminmousa


با عرض سلام در يكي از پروژه هاي طبقه بندي سرطان پوست نياز به مشاركت داريم. جايگاه نفر سوم خالي مي باشد.

🔸🔻🔸🔻🔸🔻🔻
@Raminmousa




📃Can social network analysis contribute to supply chain
management? A systematic literature review and
bibliometric analysis


📎 Study paper


@Machine_learn


DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Paper: https://arxiv.org/pdf/2401.02954v1.pdf

Code: https://github.com/deepseek-ai/deepseek-llm

Dataset: AlignBench


@Machine_learn


OpenAI o3-mini System Card

📚 Reed

@Machine_learn


اخرین زمان برای مشارکت در این پروژه تا اخر شب...!
@Raminmousa




𝗡𝗟𝗣_𝘄𝗶𝘁𝗵_𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀.pdf
8.2Мб
Natural Language Processing with Transformers Building Language Applications
with Hugging Face

#Book

@Machine_learn


International AI Safety Report

📚 Report

@Machine_learn

Показано 20 последних публикаций.