ICML 2024 best paper出炉!Google赢麻了 🫱点这里加入18个细分方向交流群(🔥巨推荐)🫲 ICML2024大会于上周日(7.21)在奥地利召开,并且于昨日(7.24)正式公开best paper与test of time奖项,多项工作为AIGC方向的成就,其中半数以上获奖一作来自Google AI。 ...
ensuring the explainability of their predictions remains a challenge. To address this, graph rationalization methods have been introduced to generate concise subsets of the original graph, known as rationales, which serve to explain the predictions made by GNNs. Existing rationalization...
Submission of Full Paper : October 30, 2024 Notification of Acceptance : November 20, 2024 Submission of Camera Ready Papers:December 9,2024 Late Registration Deadline : December 10, 2024 Conference Dates : December 12-13, 2024 Call For Papers ...
计算机视觉领域来看,大部分都默默无闻了近十几年来,CV三大会(CVPR、ICCV、ECCV)的best paper中目前仍然有影响力的,基本上都有何… 赞同 40021 条评论 分享 收藏喜欢 发ICML和NIPS的人的数理基础需要达到哪种水平? Zhanxing Zhu ...
针对这一问题,他们提出了一种创新的文档处理策略——最佳适配打包 (Best-fit Packing),通过优化文档组合来消除不必要的文本截断,并显著地提升了模型的性能且减少模型幻觉。这一研究已被 ICML 2024 接收。 论文标题: Fewer Truncations Improve Language Modeling ...
AI researcher and engineer Charles Martin took to LinkedIn to share his disappointment about his paper being rejected. He, too, like the other authors, questioned the review process. “Got our ICML rejection letters last night for our latest weight watcher papers. The general theme is that th...
[04.18.2024]🔥🔥 We have released the source code and the DoRA weight for reproducing the results in our paper! [03.20.2024]🔥🔥 DoRA is now fully supported by the HuggingFace PEFT package and can now support Linear, Conv1d, and Conv2d layers, as well as linear layers quantized wi...
This is the official code for the paper “ReconBoost: Boosting Can Achieve Modality Reconcilement.” accepted by International Conference on Machine Learning (ICML2024). This paper is available at here.Paper Title: ReconBoost: Boosting Can Achieve Modality Reconcilement.Authors...
首先,第一个策略仍然是基于历史所有数据跑个 dpo 或者 rlhf 的数据,某种意义上是基于数据我们能做的 best-guess; 关键在于第二个策略的选择,它需要去最大化它与策略 1 的 feature difference 对应的不确定性。换句话说,如果基于历史,我对这个方向仍然数据很少,没有太多信息,我就应当往这个方向多采一些数据来鼓...
It helps to make your paper look like it comes from some bigshot labs. There are certain papers that some labs always cite / arguments they often bring / words they prefer. It's much harder to shut down a presumably bigshot professor than a nobody. ...