时长：
24分钟
播放：
86
发布：
1周前
主播...
简介...
00:41:15 AI防忽悠指南：如何让聪明的机器不说胡话？
00:05:37 想变强？别再刷旧题了，你得学会自己“造”难题
00:10:06 AI进阶的秘密：一行代码如何让“学霸”真正开窍？
00:14:46 AI的新玩法：从“搬运工”到“侦探”
00:19:10 AI也会“想太多”？聊聊如何给模型一颗“定心丸”
本期介绍的五篇论文：
[CL] Learning to Reason for Factuality
[FAIR at Meta]
https://arxiv.org/abs/2508.05618
---
[CL] MathSmith: Towards Extremely Hard Mathematical Reasoning by Forging Synthetic Problems with a Reinforced Policy
[Tsinghua University]
https://arxiv.org/abs/2508.05592
---
[LG] On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification
[Southeast University & University of California, Los Angeles]
https://arxiv.org/abs/2508.05629
---
[LG] GRAIL: Learning to Interact with Large Knowledge Graphs for Retrieval Augmented Reasoning
[Tsinghua University]
https://arxiv.org/abs/2508.05498
---
[CL] Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression
[Peking University & The Hong Kong University of Science and Technology]
https://arxiv.org/abs/2508.05337
00:05:37 想变强？别再刷旧题了，你得学会自己“造”难题
00:10:06 AI进阶的秘密：一行代码如何让“学霸”真正开窍？
00:14:46 AI的新玩法：从“搬运工”到“侦探”
00:19:10 AI也会“想太多”？聊聊如何给模型一颗“定心丸”
本期介绍的五篇论文：
[CL] Learning to Reason for Factuality
[FAIR at Meta]
https://arxiv.org/abs/2508.05618
---
[CL] MathSmith: Towards Extremely Hard Mathematical Reasoning by Forging Synthetic Problems with a Reinforced Policy
[Tsinghua University]
https://arxiv.org/abs/2508.05592
---
[LG] On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification
[Southeast University & University of California, Los Angeles]
https://arxiv.org/abs/2508.05629
---
[LG] GRAIL: Learning to Interact with Large Knowledge Graphs for Retrieval Augmented Reasoning
[Tsinghua University]
https://arxiv.org/abs/2508.05498
---
[CL] Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression
[Peking University & The Hong Kong University of Science and Technology]
https://arxiv.org/abs/2508.05337
评价...
空空如也
小宇宙热门评论...
暂无小宇宙热门评论
