Nicolay Rusnachenko

nicolay-r

12 28 45

https://nicolayr.com/

AI & ML interests

NLP for Healthcare ⚕️ @BU_Research・PhD in NLP / IR ・Textual Information Retrieval

Recent Activity

upvoted an article 10 days ago

Security incident disclosure — July 2026

liked a dataset 20 days ago

oxford-llms/ai-respondents-challenge

liked a model about 1 month ago

google/medgemma-27b-it

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posted an update about 1 month ago

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📢 For those who is the field of Sentiment Analysis / Opinion Extraction / IR. So far I attend the 5 days Agent development course and honestly learned alot from trying out SKILLS and tools integration into Goodle ADK.

The course assumed to implement the project, so I am writing to share ARExplorer, -- is an agentic version of the workflow elements (NER + text classfiication + graph operations) in a form of the demo for the 5 day agent development course. This is a successor of the ARElight tool (https://github.com/nicolay-r/ARElight) that provides workflow and graph operation tools for visualizing large documents.

If you're inetersted, inviting you to checkout the quick overview:
📺️ Demo: https://youtu.be/A4ESKHX5CKU
🧑‍💻 Repo: https://github.com/nicolay-r/ARExplorer

posted an update 4 months ago

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📢 For those who experimening with large language models in clinical domain, this might be relevant. So far we participated in Task 4 of the ArchEHR-QA 2026 shared task. The task requires aligning answers to patient questions with clinical evidence. Our approach encodes clinical reasoning principles directly into the prompt, evaluated in a zero-shot setting.

Results: +2% improvement with ChatGPT-5.2. No measurable gain with Llama-3 70B, indicating the approach benefits larger-scale models.

🌟 Code: https://github.com/nicolay-r/ArchEHR-QA-2026-Task-4-MedEvi-NS
📊 Shared task: https://www.codabench.org/competitions/13528/

posted an update 5 months ago

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📢 I know this space is mosly for sharing works, but in this case I am open to work 💼🇬🇧

I know there are outstanding research labs and teams following this space 🙌

I would genuinely love to learn on ways to contribute, learn from strong lab environments, and help shape ideas into working systems.

What I bring (https://nicolayr.com):
• Applied NLP & deployment LLM-powered worflows with reasoning for IR (LangChain, LiteLLM)
• Architectures Engeneering: Transformers and / or backends (PyTorch, Tensorflow, flaxformer)
• End-to-end engineering: Frontend (JS, ReactJS) → Backend REST APIs (FastAPI) / Keycloak → Docker / NGINX → Cloud / MLOps
• Domain-specific experience in Healthcare (deploy & handle: DICOM-SR/SEG, NIFTI, databases: ORTHANC, Frontend: OHIF / cornerstone)
• Pasion about open-source NLP tooling for handling data (https://github.com/nicolay-r)

Would be happy to connect or hear any relevant suggestions on seeking for team 🧩

2 replies

posted an update 6 months ago

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📢 Who want's to have a quick start for adapting CoT schema for any LLM, this post would be relevant.

Excited to share a new version of 🌟 bulk-chain 🌟!
Bulk-chain is high-level wrapper over LLM providers for efficient quering LLMs hosted by third-party services.
It brings native batching via support of async clients.

🌟 https://github.com/nicolay-r/bulk-chain/tree/master

What's new:
☑️ Simplified inference setup
The API is now closer to the OpenAI paradigm for toggling streaming.
Instead of separate patterns in 1.2.0, now it is possible to simple toggles to enable streaming and async behavior.
☑️ 🛠️ Fixed issues when passing code contain {} blocks
☑️ 🛠️ Async streaming + batching now works properly
☑️ 🛠️ Logging of prompts could be disabled

https://github.com/nicolay-r/bulk-chain

🚨 Guys, I am open to work as developer / researcher in AI / NLP / IR in the UK 🇬🇧

🌟 Feel free to support bulk-chain on Github if you like so, or this post.
It helps alot!

reacted to prithivMLmods's post with 👍 7 months ago

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Update: TRELLIS.2 (Text to 3D, Image to 3D) Gradio with Rerun Embedded demo with improved visualization of the 3D model previewer is now available on Hugging Face. Generate assets and view them in the 3D viewer, powered and streamlined with Microsoft’s TRELLIS.2 and Tongyi-MAI’s Z-Image-Turbo models.

🤗 TRELLIS.2 (Demo): prithivMLmods/TRELLIS.2-Text-to-3D
🕹️ GitHub: https://github.com/PRITHIVSAKTHIUR/TRELLIS.2-Text-to-3D-RERUN
🕹️ Collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations

To know more about it, visit the app page or the respective model page!

reacted to MikeDoes's post with 🔥 7 months ago

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What if an AI agent could be tricked into stealing your data, just by reading a tool's description? A new paper reports it's possible.

The "Attractive Metadata Attack" paper details this stealthy new threat. To measure the real-world impact of their attack, the researchers needed a source of sensitive data for the agent to leak. We're proud that the AI4Privacy corpus was used to create the synthetic user profiles containing standardized PII for their experiments.

This is a perfect win-win. Our open-source data helped researchers Kanghua Mo, 龙昱丞, Zhihao Li from Guangzhou University and The Hong Kong Polytechnic University to not just demonstrate a new attack, but also quantify its potential for harm. This data-driven evidence is what pushes the community to build better, execution-level defenses for AI agents.

🔗 Check out their paper to see how easily an agent's trust in tool metadata could be exploited: https://arxiv.org/pdf/2508.02110

#OpenSource
#DataPrivacy
#LLM
#Anonymization
#AIsecurity
#HuggingFace
#Ai4Privacy
#Worldslargestopensourceprivacymaskingdataset

posted an update 7 months ago

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🚨 For those who intereseted in developing System + GUI for representing opinions from text, this post might be relevant. I recently brought the support for LLM in ARElight -- opinion extraction framework. ARElight is a no-string pipeline for retrieving information from large texts. It features the flexible customizations for Text Processing, NER, text translation, and relations classification.

🌟 https://github.com/nicolay-r/ARElight

This now contributes to the most effective structuring of the pipeline to text translation, name identity recognition and information retrieval.

🥞 Stack:
🌟 bulk-translate: https://github.com/nicolay-r/bulk-translate
🌟 bulk-ner: https://github.com/nicolay-r/bulk-ner
🌟 bulk-chain: https://github.com/nicolay-r/bulk-chain

Powered by AREkit:
🌟 AREkit: https://github.com/nicolay-r/AREkit

posted an update 7 months ago

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Time-Effective LLM Querying in Information Retrieval Tasks

🎤 Last week at Research Colloquium in Technische Universität Chemnitz, we presented a framework for time-effective data handling with prompting schemas. The video of the talk is now available 👇️

🎬️ Video: https://youtu.be/pa8jGOhHViI
🌟 Framework (bulk-chain): https://github.com/nicolay-r/bulk-chain

🔑 bulk-chain solves the following problems:
✅ Effective handling CoT schema with big amount of prompts and parameters they are based on (batching policies)
✅ Easy-to-apply for data-iterators (datasets handling)

posted an update 7 months ago

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📢 If you do studies in Natural Language Processing, this may be of interest.
The International Conference on Natural Language Processing (ICNLP) 🇨🇳 is comming in 2026.
This time it is going to be the 8th edition, and for those who interested in submission, call is open until 30'th of december
https://www.icnlp.net/

reacted to victor's post with 🔥 8 months ago

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Nvidia is on a roll lately. Nemotron 3 Nano is my new fav local model, but here's the real flex: they published the entire evaluation setup. Configs, prompts, logs, all of it. This is how you do open models 🔥

https://huggingface.co/blog/nvidia/nemotron-3-nano-evaluation-recipe

reacted to sergiopaniego's post with 🚀 8 months ago

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Google DeepMind releases FunctionGemma, a 240M model specialized in 🔧 tool calling, built for fine-tuning

TRL has day-0 support. To celebrate, we’re sharing 2 new resources:

> Colab guide to fine-tune it for 🌐 browser control with BrowserGym OpenEnv
> Standalone training script

> Colab notebook: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_functiongemma_browsergym_openenv.ipynb
> Training script: https://github.com/huggingface/trl/blob/main/examples/scripts/openenv/browsergym_llm.py (command to run it inside the script)
> More notebooks in TRL: https://huggingface.co/docs/trl/example_overview#notebooks

reacted to YatharthS's post with 🚀 8 months ago

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🤯 🤯 Released a high quality finetuned LLM based TTS model that can generate realistic and clear 48khz audio at over 100x realtime speed! 🤯 🤯

Github link: https://github.com/ysharma3501/MiraTTS

Model link: https://github.com/ysharma3501/MiraTTS

Blog explaining llm tts models: https://huggingface.co/blog/YatharthS/llm-tts-models

4 replies

reacted to prithivMLmods's post with 🔥 8 months ago

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Introducing the Z Image Turbo LoRA DLC App, a gallery space for plug-and-play Z-Image-Turbo LoRAs. It features a curated collection of impressive LoRAs for generating high-quality images. By default, it runs on the base model. Simply choose a LoRA, type your prompt, and generate images. You can find the app and more details below. 🤗🧪

● Space [Demo]: prithivMLmods/Z-Image-Turbo-LoRA-DLC
● Collection: https://huggingface.co/collections/prithivMLmods/image-generation-apps-collection
● Check the list of Z-Image LoRA's: https://huggingface.co/models?other=base_model:adapter:Tongyi-MAI/Z-Image-Turbo
● Github: https://github.com/PRITHIVSAKTHIUR/Z-Image-Turbo-LoRA-DLC

Other related image gen spaces:-

● FLUX-LoRA-DLC2: prithivMLmods/FLUX-LoRA-DLC2
● FLUX-LoRA-DLC: prithivMLmods/FLUX-LoRA-DLC
● Qwen-Image-LoRA-DLC: prithivMLmods/Qwen-Image-LoRA-DLC
● Qwen-Image-Edit-2509-LoRAs-Fast: prithivMLmods/Qwen-Image-Edit-2509-LoRAs-Fast
● Qwen-Image-Edit-2509-LoRAs-Fast-Fusion: prithivMLmods/Qwen-Image-Edit-2509-LoRAs-Fast-Fusion

& more...

To know more about it, visit the app page or the respective model page!

2 replies

reacted to ZennyKenny's post with 👍 8 months ago

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🍓 One of the coolest parts about being an early Strawberry user has been the opportunity to build on the app at the ground floor.

The platform already has a ton of great integrations that let you interact with your external apps directly with tools, but I wanted to add the ability to do stuff in Slack as well.

💪 So I took the base Anthropic Slack MCP server, added a whole bunch of new tools, and generalized it as an HTTP-based SSE-server and deployed it in like 2 minutes with Railway so that Strawberry could make use of it (as can Claude or any other MCP client).

Now, you can Chat with your Strawberry Companion (or Claude, or whatever) and do things like:
➡️ Get caught up across all of your Slack channels after a long weekend or noisy incident without having to read 20 threads in 10 different channels
➡️ Create, read, and edit Canvases, Messages, and Channels
➡️ Take any resources or content that you're using in your Chat and inject it directly into Slack without copy / paste

😎 I'm pretty pleased with the results, and I made a short demo video showing the results of the work (link in comments). The best part is, it's available on GitHub for anyone else to use too (link in the comments, instructions in the README). The setup takes about 5-10 minutes.

2 replies

replied to ronantakizawa's post 8 months ago

@ronantakizawa , keeping in mind about that resource, so perhabs would be suitable in the side projects.
I would also raise interest here on having a look on the ongoing studies once they would be wrapped up and publised.

reacted to unmodeled-tyler's post with 🚀 8 months ago

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New Preview Model: https://huggingface.co/spaces/unmodeled-tyler/vanta-research-loux-preview

VANTA Research is excited to announce a small lab preview of our new 675B fine tune, Loux-Large. Loux is an AI model with a sophisticated, rebellious edge designed to assist and collaborate with engineers, builders, and people working on technical projects.

If you enjoy working with Loux and would like full access, let us know by liking the space or opening a discussion in the community!

4 replies

reacted to davidberenstein1957's post with 🚀 8 months ago

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🚨 Phare LLM benchmark V2: Reasoning models don't guarantee better security

Read the full blog here: https://huggingface.co/blog/davidberenstein1957/phare-llm-benchmark-v2

reacted to Reubencf's post with 🔥 8 months ago

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Great News !
Reubencf/Nano_Banana_Editor Now supports black-forest-labs/FLUX.1-Kontext-dev and Qwen/Qwen-Image-Edit-2509

Just log in with Huggingface and try it out

replied to ronantakizawa's post 8 months ago

@ronantakizawa , such a good resource for exploring the traits of the top developers under various angles!
In the context of the projects around it, I couldn't find the existing studies that were based on these data sets (which is not yet publicly available I believe).
So I was wonder, are there any potential plants where these datasets would be useful in the context of research?

reacted to ronantakizawa's post with 🚀 8 months ago

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Introducing the github-top-developers dataset: A comprehensive dataset of the top 8000 developers on GitHub (2020-2025). This dataset captures the evolution of GitHub's trending developers repositories over time and the projects they work on.

#github #developers

ronantakizawa/github-top-developers

4 replies

Nicolay Rusnachenko

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