5 papers
SCOPD: Sparse-Context On-Policy Self-Distillation for Efficient Vision-Language Models
Ahmadreza Jeddi, Enming Zhang, Jasper Gerigk +12
Reasoning vision-language models (VLMs) process images and videos as long sequences of visual tokens, making inference expensive. Training-free token pruning reduces this cost, but…
AVIS: Adaptive Test-Time Scaling for Vision-Language Models
Ahmadreza Jeddi, Minh Ngoc Le, Amirhossein Kazerouni +8
Modern Vision-Language Models (VLMs) benefit from chain-of-thought prompting and test-time scaling, but these gains often come with prohibitive inference cost due to large visual c…
GEAR: Genetic AutoResearch for Agentic Code Evolution
Ahmadreza Jeddi, Minh Ngoc Le, Hakki C. Karaimer +2
Autonomous research agents can already run machine learning experiments without human supervision, but many rely on a narrow search strategy: they repeatedly modify one program and…
PuzzleCraft: Exploration-Aware Curriculum Learning for Puzzle-Based RLVR in VLMs
Ahmadreza Jeddi, Hakki Can Karaimer, Hue Nguyen +8
RL post-training with verifiable rewards (RLVR) has become a practical route to eliciting chain-of-thought reasoning in vision--language models (VLMs), but scaling it in the visual…
Off the Planckian Locus: Using 2D Chromaticity to Improve In-Camera Color
SaiKiran Tedla, Joshua E. Little, Hakki Can Karaimer +1
Traditional in-camera colorimetric mapping relies on correlated color temperature (CCT)-based interpolation between pre-calibrated transforms optimized for Planckian illuminants su…