10 papers
Marchuk: Efficient Global Weather Forecasting from Mid-Range to Sub-Seasonal Scales via Flow Matching
Arsen Kuzhamuratov, Mikhail Zhirnov, Andrey Kuznetsov +2
Accurate subseasonal weather forecasting remains a major challenge due to the inherently chaotic nature of the atmosphere, which limits the predictive skill of conventional models…
CADEvolve: Creating Realistic CAD via Program Evolution
Maksim Elistratov, Marina Barannikov, Gregory Ivanov +4
Computer-Aided Design (CAD) delivers rapid, editable modeling for engineering and manufacturing. Recent AI progress now makes full automation feasible for various CAD tasks. Howeve…
CoMa: Contextual Massing Generation with Vision-Language Models
Evgenii Maslov, Valentin Khrulkov, Alexandra Vabnits +6
Context-aware building massing is an important early-stage design task: given a site for buildings, a generated massing should not only fit the target parcel, but also relate to th…
GigaEvo: An Open Source Optimization Framework Powered By LLMs And Evolution Algorithms
Valentin Khrulkov, Andrey Galichin, Denis Bashkirov +5
Recent advances in LLM-guided evolutionary computation, particularly AlphaEvolve (Novikov et al., 2025; Georgiev et al., 2025), have demonstrated remarkable success in discovering…
Multi-Agent GraphRAG: A Text-to-Cypher Framework for Labeled Property Graphs
Anton Gusarov, Anastasia Volkova, Valentin Khrulkov +3
While Retrieval-Augmented Generation (RAG) methods commonly draw information from unstructured documents, the emerging paradigm of GraphRAG aims to leverage structured data such as…
Speech-to-LaTeX: New Models and Datasets for Converting Spoken Equations and Sentences
Dmitrii Korzh, Dmitrii Tarasov, Artyom Iudin +6
Conversion of spoken mathematical expressions is a challenging task that involves transcribing speech into a strictly structured symbolic representation while addressing the ambigu…
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models
Pengyi Li, Matvey Skripkin, Alexander Zubrey +2
Large language models (LLMs) excel at reasoning, yet post-training remains critical for aligning their behavior with task goals. Existing reinforcement learning (RL) methods often…
Listener-Rewarded Thinking in VLMs for Image Preferences
Alexander Gambashidze, Li Pengyi, Matvey Skripkin +5
Training robust and generalizable reward models for human visual preferences is essential for aligning text-to-image and text-to-video generative models with human intent. However,…
Test-Time Reasoning Through Visual Human Preferences with VLMs and Soft Rewards
Alexander Gambashidze, Konstantin Sobolev, Andrey Kuznetsov +1
Can Visual Language Models (VLMs) effectively capture human visual preferences? This work addresses this question by training VLMs to think about preferences at test time, employin…
MaxInfo: A Training-Free Key-Frame Selection Method Using Maximum Volume for Enhanced Video Understanding
Pengyi Li, Irina Abdullaeva, Alexander Gambashidze +2
Modern Video Large Language Models (VLLMs) often rely on uniform frame sampling for video understanding, but this approach frequently fails to capture critical information due to f…