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Boris Orekhov

nevmenandr
lostalien89's profile picture webxos's profile picture Achiando's profile picture
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https://nevmenandr.github.io/portfolio/

AI & ML interests

Natural Language Processing, Poetry Generation, Linguistics, Low-resource languages

Recent Activity

posted an update about 15 hours ago
https://huggingface.co/nevmenandr/char-based-lstm-russian-poetry-pasternak 🧠 LSTM Language Model Visualization: A Deep Dive into Char-RNN 📊 Model Architecture at a Glance - Model Type: 5-layer LSTM - Hidden Size: 512 - Vocabulary: 137 characters - Sequence Length: 50 - Total Parameters: ~9.8 million - Training: 50 epochs, 10,750 iterations - Final Validation Loss: 1.1266 - The model learned to generate Pasternak-style poetry - pretty impressive for a char-rnn! 🎨 The Beautiful Mess Check out this heatmap visualization - it's like a Persian carpet! 🏠✨ - Each gate has its own patterns: - Input Gate: Controls what new info enters the cell - Forget Gate: Decides what to discard - Cell Gate: Creates new candidate values - Output Gate: Determines what to output - The weights show beautiful structured patterns - different gates learned distinct strategies for processing text.https://huggingface.co/papers/2306.02771
posted an update 10 days ago
🔥 New Russian Stylometry Dataset! Russian Stylometric Dataset (RSD) — 322 texts from the 19th – early 20th centuries (16 million words), prepared for analysis in stylo (R) and machine learning (Python). 📚 What's inside? Fiction, journalism, scientific texts, drama, poetry Grouped by author, gender, age, genre, literary movements (Romanticism/Realism) Character speech (Tolstoy, Gogol, Ostrovsky) Generated texts (LSTM, GPT) 📊 Use cases: authorship attribution, clustering, classification, benchmarking methods. 🔓 Public domain + GPL-3.0 license. 👉 Learn more: https://github.com/nevmenandr/RSD DOI: 10.5281/zenodo.20701309
posted an update 12 days ago
https://huggingface.co/nevmenandr/char-based-lstm-russian-poetry-https://huggingface.co/nevmenandr/char-based-lstm-russian-poetry-mandelshtam https://huggingface.co/nevmenandr/char-based-lstm-russian-poetry-hexameter https://huggingface.co/papers/2306.02771 📜 RNN vs. Transformers: How an Old Architecture Better Perceives Poetic Style In the era of Transformer dominance, we often forget that old RNNs (especially character-level LSTMs) remain irreplaceable for tasks where *individual style*, rhythm, and micro-patterns matter. These three models are clear proof of that. 🎯 Why does this matter today? - **Stylistic analysis**: RNNs better capture meter, repetitions, and unexpected tonal shifts. - **Teaching poetics**: generating "almost correct" but hallucinating lines helps explore the boundaries of style. - **Nostalgia and replication**: a reminder that not everything is measured by BLEU and perplexity. 🖼️ Visualization Attached is an infographic comparing the three models (architecture, style, generation sample). > RNNs aren't dead. They're just writing poetry in silence.
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