Some of the presentations and articles I took part in. Updates from time to time
! My always updated CV 🤗 ! github; gdocs
Implicit Context Condensation for Local SWE Agents - presentation of my Master's Thesis. Made in 2025.
text
The overview of the State-Space Models - ICML-style review of 3 essential works on SSMs. SSM_overview (Jan 2025).
Three overviewed papers are:1) HiPPO: Recurrent Memory with Optimal Polynomial Projections by A. Gu et. al.
2) Resurrecting Recurrent Neural Networks for Long Sequences by A. Orvieto et. al.
3) Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention by A. Katharopoulos et. al.
Improving Convolutional Occupancy Networks - Paper describing what we have done in a team during ML43D course at TUM. Github with improvements.
We modified ConvONets and improved the results on restoration of 3D objects by 10%. convONets_3d_modifications (Jan 2025).
[MASTER] Multi-Agent Sales-Tailored Expert Robot - presentation, review of our project from hackathon [MASTER] (Apr 2024).
gdocs link
Annotated OctoPack: Instruction Tuning Code Large Language Models paper (Dec 2023).
Annotated CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning paper (Dec 2021).
Empirical Study of Transformers for Symbolic Mathematics - presentation of my Bachelor's Thesis. Made in 2021.
gdocs link for work in PDF
Training language GANs from Scratch - presentation, review of Cyprien de Masson d'Autume, Mihaela Rosca, Jack Rae, Shakir Mohamed (NeurIPS 2019). Review made in March 2021.
gdocs link
Transformer-based Source Code Summarization - report on my summer project (made in 2020). Includes review of summarization transformer-based methods and implementation of GGNN.
Gradient_Estimation_with_Stochastic_Softmax_Tricks - presentation, review of Max B. Paulus et al. (NeurIPS 2020). Review made in November 2020.
gdocs link
corpus_NL2ML_Presentation - presentation for course work corpus NL2ML. Made for NL2ML corpus in 2020.
Feature selection and extraction - pre-neural methods for selection and extracion of features https://github.com/Kirili4ik/Selection-Extraction
Adversarial_examples - presentation, review of basic adversarial examples methods (made in 2019)
Review_on_paper_Facebook - review Xinran He et al. (2014), Practical Lessons from Predicting Clicks on Ads at Facebook (review made in 2018)