想不想知道,如何通过一场“团体赛”规则,治好AI“偏科”的毛病?又如何不花一分钱,只靠一个古老的“背包问题”,就让AI训练效率飙升40%?甚至,我们将看到一个天生“失明”的AI,如何在想象力测试中击败人类。本期节目,我们将从最新的几篇论文出发,揭示AI如何学会团队合作、聪明用钱,甚至掌握了“蒙眼思考”和“断舍离”的智慧。00:00:32 AI训练指南:如何让你的“学霸”不偏科?00:05:50 AI训练的“免费午餐”:如何不花一分钱,让模型变得更聪明?00:11:57 从“一指禅”到“组合拳”:AI学习的升级之路00:16:54 AI的“心灵盲区”:它看不见,却想得更明白?00:21:19 AI的记忆难题:如何优雅地“断舍离”?本期介绍的几篇论文:[LG] Polychromic Objectives for Reinforcement Learning [Stanford University] https://arxiv.org/abs/2509.25424 ---[LG] Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation [ByteDance Seed & The Chinese University of Hong Kong] https://arxiv.org/abs/2509.25849 ---[LG] Learning to Reason as Action Abstractions with Scalable Mid-Training RL [Apple] https://arxiv.org/abs/2509.25810 ---[LG] Artificial Phantasia: Evidence for Propositional Reasoning-Based Mental Imagery in Large Language Models [Northeastern University] https://arxiv.org/abs/2509.23108 ---[LG] Expected Attention: KV Cache Compression by Estimating Attention from Future Queries Distribution [NVIDIA & Sapienza University of Rome] https://arxiv.org/abs/2510.00636
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