Machine learning books and papers pinned «با عرض سلام می خواهیم مقاله ی جدیدی را تحت عنوان زیر شروع کنیم: Comparative survey on Transfer Learning for multi-modal wound image classification مقالات قبلی که در این رابطه نوشتیم به ترتیب زیر می باشند: تیم 1: [1]چاپ شده در Expert system with application…»
Forwarded from Github LLMs
Signatures of unconventional superconductivity near reentrant and fractional quantum anomalous Hall insulators
📚 Paper
@Machine_learn
📚 Paper
@Machine_learn
BioPars: Persian biomedical data
Model: BioPars
Dataset: ParsMed
Benchmark: BioParsQa
Next week submit
@Machine_learn
Model: BioPars
Dataset: ParsMed
Benchmark: BioParsQa
Next week submit
@Machine_learn
هدف اين كانال حل مشكل سايت زني به مقالات. از طرفي كساني كه نيازمند هزينه سايت هستن نيز مي تونن با سايت زدن به هر مقاله ي اين كانال بخشي از هزينه رو دريافت كنن.
https://www.tg-me.com/papercite
https://www.tg-me.com/papercite
Telegram
Paper cite
ارسال مقاله جهت سايت
@Raminmousa
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هدف اين كانال حل مشكل سايت زني به مقالات. از طرفي كساني كه نيازمند هزينه سايت هستن نيز مي تونن با سايت زدن به هر مقاله ي اين كانال بخشي از هزينه رو دريافت كنن.
@Raminmousa
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هدف اين كانال حل مشكل سايت زني به مقالات. از طرفي كساني كه نيازمند هزينه سايت هستن نيز مي تونن با سايت زدن به هر مقاله ي اين كانال بخشي از هزينه رو دريافت كنن.
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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
🖥 Github: https://github.com/deepmodeling/crystalformer
📕 Paper: https://arxiv.org/abs/2504.02367v1
🔗 Dataset: https://paperswithcode.com/dataset/alex-20
@Machine_learn
4 advanced attention mechanisms you should know:
• Slim attention — 8× less memory, 5× faster generation by storing only K from KV pairs and recomputing V.
• XAttention — 13.5× speedup on long sequences via "looking" at the sum of values along diagonal lines in the attention matrix.
• Kolmogorov-Arnold Attention, KArAt — Adaptable attention with learnable activation functions using KANs instead of softmax.
• Multi-token attention (MTA) — Lets the model consider groups of nearby words together for smarter long-context handling.
Read the overview of them in our free article on https://huggingface.co/blog/Kseniase/attentions
@Machine_learn
• Slim attention — 8× less memory, 5× faster generation by storing only K from KV pairs and recomputing V.
• XAttention — 13.5× speedup on long sequences via "looking" at the sum of values along diagonal lines in the attention matrix.
• Kolmogorov-Arnold Attention, KArAt — Adaptable attention with learnable activation functions using KANs instead of softmax.
• Multi-token attention (MTA) — Lets the model consider groups of nearby words together for smarter long-context handling.
Read the overview of them in our free article on https://huggingface.co/blog/Kseniase/attentions
@Machine_learn
Forwarded from Papers
با عرض سلام برای یکی از مقالاتمون نیازمند نفر اول داریم که co-author مقاله هم باشه.
مجله ی ارسالی scientific report natue
https://www.nature.com/srep/
می باشد.
شرایط واگذاری رو در صورت نیاز می تونین با ایدی بنده ست کنین.
@Raminmousa
@Machine_learn
@Paper4money
مجله ی ارسالی scientific report natue
https://www.nature.com/srep/
می باشد.
شرایط واگذاری رو در صورت نیاز می تونین با ایدی بنده ست کنین.
@Raminmousa
@Machine_learn
@Paper4money
Nature
Scientific Reports
Scientific Reports publishes original research in all areas of the natural and clinical sciences. We believe that if your research is scientifically valid and ...
Machine learning books and papers pinned «با عرض سلام برای یکی از مقالاتمون نیازمند نفر اول داریم که co-author مقاله هم باشه. مجله ی ارسالی scientific report natue https://www.nature.com/srep/ می باشد. شرایط واگذاری رو در صورت نیاز می تونین با ایدی بنده ست کنین. @Raminmousa @Machine_learn…»
CPPO: Accelerating the Training of Group Relative Policy Optimization-Based Reasoning Models
28 Mar 2025 · Zhihang Lin, Mingbao Lin, Yuan Xie, Rongrong Ji
Paper: https://arxiv.org/pdf/2503.22342v1.pdf
Code: https://github.com/lzhxmu/cppo
Datasets: GSM8K - MATH
@Machine_learn
28 Mar 2025 · Zhihang Lin, Mingbao Lin, Yuan Xie, Rongrong Ji
Paper: https://arxiv.org/pdf/2503.22342v1.pdf
Code: https://github.com/lzhxmu/cppo
Datasets: GSM8K - MATH
@Machine_learn
با عرض سلام دوره ی خصوصی SYFA را داریم برگذار میکنیم که هدف نحوه اشنایی با فرایند نگارش و چاپ مقالات می باشد. جلسات ۱ ساعته و خصوصی می باشند. که هر هفته به ازای هر شخص ۲ جلسه برگذار خواهد شد. جهت ثبت نام و ست کردن زمان با ایدی بنده در ارتباط باشین.
@Raminmousa
@Raminmousa
Data-engineer-handbook
This is a repo with links to everything you'd ever want to learn about data engineering
Creator: DataExpert-io
Stars ⭐️: 24.9k
Forked by: 4.9k
Github Repo:
https://github.com/DataExpert-io/data-engineer-handbook
#github
➖➖➖➖➖➖➖➖➖➖➖➖➖➖
@Machine_learn
This is a repo with links to everything you'd ever want to learn about data engineering
Creator: DataExpert-io
Stars ⭐️: 24.9k
Forked by: 4.9k
Github Repo:
https://github.com/DataExpert-io/data-engineer-handbook
#github
➖➖➖➖➖➖➖➖➖➖➖➖➖➖
@Machine_learn
GitHub
GitHub - DataExpert-io/data-engineer-handbook: This is a repo with links to everything you'd ever want to learn about data engineering
This is a repo with links to everything you'd ever want to learn about data engineering - DataExpert-io/data-engineer-handbook
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⛽ VoRA: Vision as LoRA ⛽
#ByteDance introduces #VoRA (Vision as #LoRA) — a novel framework that transforms #LLMs into Multimodal Large Language Models (MLLMs) by integrating vision-specific LoRA layers.
All training data, source code, and model weights are openly available!
Key Resources:
Overview: https://t.ly/guNVN
Paper: arxiv.org/pdf/2503.20680
GitHub Repo: github.com/Hon-Wong/VoRA
Project Page: georgeluimmortal.github.io/vora-homepage.github.io
@Machine_learn
#ByteDance introduces #VoRA (Vision as #LoRA) — a novel framework that transforms #LLMs into Multimodal Large Language Models (MLLMs) by integrating vision-specific LoRA layers.
All training data, source code, and model weights are openly available!
Key Resources:
Overview: https://t.ly/guNVN
Paper: arxiv.org/pdf/2503.20680
GitHub Repo: github.com/Hon-Wong/VoRA
Project Page: georgeluimmortal.github.io/vora-homepage.github.io
@Machine_learn