Sep 3, 2026 · Artificial Intelligence

EASE: Teaching Multimodal RL Where to Look, Not Just What to Answer

EASE introduces evidence-anchored spatial attention supervision to multimodal reinforcement learning with verifiable rewards, using annotated evidence bounding boxes to guide model attention toward relevant image regions during training, improving accuracy on visual reasoning benchmarks without inference overhead.

Attention MechanismEMNLP 2026Evidence Grounding

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EASE: Teaching Multimodal RL Where to Look, Not Just What to Answer

Machine Learning Algorithms & Natural Language Processing

Jun 18, 2026 · Artificial Intelligence

UniRL: Tencent Hunyuan’s Open‑Source Framework Unifying Multimodal RL Training

UniRL is an open‑source, distributed reinforcement‑learning post‑training framework that consolidates fragmented pipelines for image, video, and language‑vision models, offering a unified rollout‑reward‑advantage‑train‑sync contract, extensive model support, built‑in algorithms, and multi‑modal reward components to lower engineering barriers in AIGC research.

Distributed TrainingLLMMultimodal RL

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UniRL: Tencent Hunyuan’s Open‑Source Framework Unifying Multimodal RL Training