KuaiRand uses randomly exposed videos with 12 user signals, enabling unbiased recommendation evaluation.

Chongming Gao, Shijun Li, Yuan Zhang et al.

Proposes RAN models with adjustable non-linearity, achieving hardware-efficient deep networks; RAN-e and RAN-i outperform baselines on ImageNet and hardware benchmarks.

Kartikeya Bhardwaj, James Ward, Caleb Tung et al.

This study models recommendation system scaling laws, revealing performance follows a power law plus constant, with data size being the dominant factor.

Newsha Ardalani, Carole-Jean Wu, Zeliang Chen et al.

Using model-free RL (SAC, DroQ) with regularization, a quadruped learns to walk in 20 minutes across diverse terrains, emphasizing system design and low-level control.

Laura Smith, Ilya Kostrikov, Sergey Levine

Adan is an adaptive Nesterov momentum optimizer achieving \(\mathcal{O}(\varepsilon^{-3.5})\) complexity, significantly speeding up deep model training.

Xingyu Xie, Pan Zhou, Huan Li et al.

RelPose predicts probabilistic relative rotations using an energy model, improving 3D reconstruction from sparse images.

Jason Y. Zhang, Deva Ramanan, Shubham Tulsiani

Introduces GCP-CROWN, combining MIP-generated cuts with bound propagation, achieving complete neural network verification with under 5 seconds per instance.

Huan Zhang, Shiqi Wang, Kaidi Xu et al.

Introduced SNIPE method to estimate TTE under network interference using low-order interactions.

Mayleen Cortez-Rodriguez, Matthew Eichhorn, Christina Lee Yu

MonoViT combines Transformer and CNN for self-supervised monocular depth estimation, achieving state-of-the-art results with Abs Rel 0.099 on KITTI.

Chaoqiang Zhao, Youmin Zhang, Matteo Poggi et al.

LATTE uses pre-trained language and vision models with Transformer to adapt 3D robot trajectories from natural language commands, no task prior needed.

Arthur Bucker, Luis Figueredo, Sami Haddadin et al.

Proposes Conformal Risk Control (CRC) algorithm extending split conformal prediction to bound the expected value of any monotone loss function, validated on vision and NLP tasks.

Anastasios N. Angelopoulos, Stephen Bates, Adam Fisch et al.

Achieved stable 3D underactuated bipedal walking using LIP model and neural adaptation.

Victor Paredes, Ayonga Hereid

Introduces optimal learning rates for regularized conditional mean embedding under misspecification using a novel vector-valued interpolation space.

Zhu Li, Dimitri Meunier, Mattes Mollenhauer et al.

Proposes Cross Attention Control for Prompt-to-Prompt image editing, enabling text-only localized and global modifications without masks, with high fidelity.

Amir Hertz, Ron Mokady, Jay Tenenbaum et al.

Proposes Textual Inversion, optimizing 3-5 images to learn new pseudo-words in frozen models, enabling personalized generation.

Rinon Gal, Yuval Alaluf, Yuval Atzmon et al.

ViP3D employs 3D agent queries for end-to-end visual trajectory prediction, outperforming traditional pipelines with significant improvements.

Junru Gu, Chenxu Hu, Tianyuan Zhang et al.

Introduces two industrial process datasets for benchmarking causal discovery algorithms, evaluated with metrics like TP, FDR, and SHD.

Giovanni Menegozzo, Diego Dall'Alba, Paolo Fiorini

Introduced DA² dataset with 9M dual-arm grasp pairs, incorporating multi-metric labels, enabling end-to-end evaluation models for robotic manipulation.

Guangyao Zhai, Yu Zheng, Ziwei Xu et al.

A novel framework using shuffled videos to address temporal bias, enhancing model generalization.

Jiachang Hao, Haifeng Sun, Pengfei Ren et al.

InterFuser uses Transformer-based sensor fusion to improve autonomous driving safety, achieving top CARLA leaderboard score of 76.18.

Hao Shao, Letian Wang, RuoBing Chen et al.