Gen-Searcher trains a search-augmented image generation agent via supervised and reinforcement learning, yielding about 16-point gains on knowledge-intensive benchmarks.
A visual-native harness with an image bank and on-policy data evolution improves multimodal deep search agents, raising Qwen3-VL-8B to 39.0% average and surpassing Gemini-2.5 Pro.
GeoSym Engine automates symbolically-verifiable geometric reasoning data synthesis, and models trained on GeoSym127K achieve large gains on diagram-dependent geometry benchmarks.
OpenSearch-VL introduces an open-source recipe training multimodal deep search agents via curated data, diverse tools, and multi-turn fatal-aware GRPO, achieving over 10-point benchmark gains comparable to proprietary models.
Unify-Agent reframes image synthesis as an agent pipeline with search and recaptioning, improving generation of long-tail factual concepts via 143K curated trajectories.