你有没有想过,AI也会有“选择困难症”吗?或者,怎么才能给AI请个既省钱又能干的“陪练”?这一期,我们就来聊聊几篇有趣的最新论文,看看科学家们是如何教会AI像高手一样反思、像侦探一样倾听“沉默的投票”,甚至用中学物理知识,给AI装上一双“3D眼睛”的。准备好了吗?让我们一起出发!
鸡娃不如“陪练”,AI训练的降本增效新思路
AI的学霸秘籍,如何像高手一样思考和进化
AI的阅读术,如何既快又好地啃下海量信息?
AI的“过分自信”,原来是种“选择困难症”
让AI拥有“立体视觉”的省钱妙计
本期介绍的几篇论文:
[LG] CoDistill-GRPO: A Co-Distillation Recipe for Efficient Group Relative Policy Optimization
[Google Research]
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[CL] RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards
[Google Cloud AI Research]
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[CL] Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models
[Google DeepMind]
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[CL] The Silent Vote: Improving Zero-Shot LLM Reliability by Aggregating Semantic Neighborhoods
[Google]
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[LG] RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings
[Seoul National University & Google Research]
![[人人能懂AI前沿] AI的学霸秘籍、省钱妙计与陪练手册](https://image.xyzcdn.net/FqWpK8fpivLboaqBbRHUe_BCOvxu.png@small)