Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization
Reinforcement learning (RL) with group-relative advantages has become the de facto standard for post-training languag...
每天自动聚合 AI 领域最新动态
Reinforcement learning (RL) with group-relative advantages has become the de facto standard for post-training languag...
Audio-Text Foundation Models (ATMs) fail catastrophically under severe acoustic noise, yet existing adaptation strate...
Learning to generate or reconstruct explorable worlds requires video paired with more than RGB: camera motion, scene ...
Despite recent advances in unified multimodal models for multi-reference image generation, existing benchmarks remain...
Scientific discovery often involves optimising expensive-to-evaluate objectives over vast, structured, and open-ended...
AI has long assisted scientific research, but the rapid advance of LLMs and agentic scaffolds is reshaping the landsc...
Motion Language Models (MoLMs) typically understand human motions by tokenizing 3D motion and processing the resultin...
We present MOSS-VL, an open vision-language model family that treats real-time interaction -- perceiving while it spe...
Instruction-based general video editing seeks to unify diverse editing operations within a single, intuitive interfac...
Clinical decision support is moving toward committees of language-model agents deliberating on a shared workspace. We...
Current large language model development relies on massive, often non-permissible datasets, creating a high barrier f...
Parliamentary proceedings are a primary record of democratic deliberation, yet their volume and fragmentation make mu...