6 papers
CoMa: Contextual Massing Generation with Vision-Language Models
Evgenii Maslov, Valentin Khrulkov, Anastasia Volkova +3
The conceptual design phase in architecture and urban planning, particularly building massing, is complex and heavily reliant on designer intuition and manual effort. To address 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…
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…
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…