3 papers
cs.CL2025
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…
cs.CV2025
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,…
cs.CV2025
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…