ML and AI papers

Scaling Laws for Downstream Task Performance of Large Language Models (AI summary)

Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo

MOMENT: A Family of Open Time-series Foundation Models (AI summary)

Mononito Goswami, Konrad Szafer, Arjun Choudhry, Yifu Cai, Shuo Li, Artur Dubrawski

MobileVLM V2: Faster and Stronger Baseline for Vision Language Model (AI summary)

Xiangxiang Chu, Limeng Qiao, Xinyu Zhang, Shuang Xu, Fei Wei, Yang Yang, Xiaofei Sun, Yiming Hu, Xinyang Lin, Bo Zhang, Chunhua Shen

Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models (AI summary)

Jianyuan Guo, Hanting Chen, Chengcheng Wang, Kai Han, Chang Xu, Yunhe Wang

LiPO: Listwise Preference Optimization through Learning-to-Rank (AI summary)

Tianqi Liu, Zhen Qin, Junru Wu, Jiaming Shen, Misha Khalman, Rishabh Joshi, Yao Zhao, Mohammad Saleh, Simon Baumgartner, Jialu Liu, Peter J. Liu, Xuanhui Wang

FindingEmo: An Image Dataset for Emotion Recognition in the Wild (AI summary)

Laurent Mertens, Elahe' Yargholi, Hans Op de Beeck, Jan Van den Stock, Joost Vennekens

Repeat After Me: Transformers are Better than State Space Models at Copying (AI summary)

Samy Jelassi, David Brandfonbrener, Sham M. Kakade, Eran Malach

Efficient Exploration for LLMs (AI summary)

Vikranth Dwaracherla, Seyed Mohammad Asghari, Botao Hao, Benjamin Van Roy

Genie: Generative Interactive Environments (AI summary)

Jake Bruce, Michael Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal Behbahani, Stephanie Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits (AI summary)