ICLR 2024 Conference Submissions

Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video
Xiangming Zhu, Huayu Deng, Haochen Yuan, Yunbo Wang, Xiaokang Yang
- Published: 16 Jan 2024, Last Modified: 21 Apr 2024
- ICLR 2024 poster
- Readers: Everyone
When and Why Momentum Accelerates SGD: An Empirical Study
Jingwen Fu, Bohan Wang, Huishuai Zhang, Zhizheng Zhang, Zhi-Ming Ma, Wei Chen, Nanning Zheng
- 22 Sept 2023 (modified: 25 Mar 2024)
- ICLR 2024 Conference Withdrawn Submission
- Readers: Everyone
Privacy-Preserving In-Context Learning for Large Language Models
Tong Wu, Ashwinee Panda, Jiachen T. Wang, Prateek Mittal
- Published: 16 Jan 2024, Last Modified: 15 Apr 2024
- ICLR 2024 poster
- Readers: Everyone
PyTorch Geometric High Order: A Unified Library for High Order Graph Neural Network
Xiyuan Wang, Muhan Zhang
- 22 Sept 2023 (modified: 11 Feb 2024)
- Submitted to ICLR 2024
- Readers: Everyone
Hardware-Friendly Post-Training Quantization: Input- and Output-Channelwise Scale and Offset
Geunjae Choi, Kamin Lee, KiYoon Yoo, Nojun Kwak
- 22 Sept 2023 (modified: 11 Feb 2024)
- Submitted to ICLR 2024
- Readers: Everyone
Masked Distillation Advances Self-Supervised Transformer Architecture Search
Caixia Yan, Xiaojun Chang, Zhihui Li, Lina Yao, Minnan Luo, Qinghua Zheng
- Published: 16 Jan 2024, Last Modified: 08 Mar 2024
- ICLR 2024 poster
- Readers: Everyone
Adaptive Self-training Framework for Fine-grained Scene Graph Generation
Kibum Kim, Kanghoon Yoon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park
- Published: 16 Jan 2024, Last Modified: 15 Mar 2024
- ICLR 2024 poster
- Readers: Everyone
DPFormer: Learning Differentially Private Transformer on Long-Tailed Data
Youlong Ding, Xueyang Wu, Hao Wang, Weike Pan
- 22 Sept 2023 (modified: 11 Feb 2024)
- Submitted to ICLR 2024
- Readers: Everyone
FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering
Yongxin Guo, Xiaoying Tang, Tao Lin
- 22 Sept 2023 (modified: 11 Feb 2024)
- Submitted to ICLR 2024
- Readers: Everyone
Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses
Chuanqing Wang, Di Wu, Chaoming Fang, Jie Yang, Mohamad Sawan
- Published: 16 Jan 2024, Last Modified: 19 Mar 2024
- ICLR 2024 poster
- Readers: Everyone
Towards Foundation Models for Knowledge Graph Reasoning
Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu
- Published: 16 Jan 2024, Last Modified: 13 Mar 2024
- ICLR 2024 poster
- Readers: Everyone
COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery
Anne Harrington, Vasha DuTell, Mark Hamilton, Ayush Tewari, Simon Stent, William T. Freeman, Ruth Rosenholtz
- Published: 16 Jan 2024, Last Modified: 15 Mar 2024
- ICLR 2024 poster
- Readers: Everyone
DIFUSCO-LNS: Diffusion-Guided Large Neighbourhood Search for Integer Linear Programming
Shengyu Feng, Zhiqing Sun, Yiming Yang
- 22 Sept 2023 (modified: 11 Feb 2024)
- Submitted to ICLR 2024
- Readers: Everyone
CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement
Mohammadreza Salehi, Mehrdad Farajtabar, Maxwell Horton, Fartash Faghri, Hadi Pouransari, Raviteja Vemulapalli, Oncel Tuzel, Ali Farhadi, Mohammad Rastegari, Sachin Mehta
- 22 Sept 2023 (modified: 25 Mar 2024)
- ICLR 2024 Conference Withdrawn Submission
- Readers: Everyone
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models
Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi
- Published: 16 Jan 2024, Last Modified: 15 Apr 2024
- ICLR 2024 poster
- Readers: Everyone
More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
James B Simon, Dhruva Karkada, Nikhil Ghosh, Mikhail Belkin
- Published: 16 Jan 2024, Last Modified: 18 Apr 2024
- ICLR 2024 poster
- Readers: Everyone
IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks
Jiarui Xu, Yossi Gandelsman, Amir Bar, Jianwei Yang, Jianfeng Gao, Trevor Darrell, Xiaolong Wang
- 22 Sept 2023 (modified: 11 Feb 2024)
- Submitted to ICLR 2024
- Readers: Everyone
SALMON: Self-Alignment with Instructable Reward Models
Zhiqing Sun, Yikang Shen, Hongxin Zhang, Qinhong Zhou, Zhenfang Chen, David Daniel Cox, Yiming Yang, Chuang Gan
- Published: 16 Jan 2024, Last Modified: 21 Apr 2024
- ICLR 2024 poster
- Readers: Everyone
Frustratingly Easy Model Generalization by Dummy Risk Minimization
Juncheng Wang, Jindong Wang, Xixu HU, Shujun Wang, Xing Xie
- 22 Sept 2023 (modified: 25 Mar 2024)
- ICLR 2024 Conference Withdrawn Submission
- Readers: Everyone
One by One, Continual Coordinating with Humans via Hyper-Teammate Identification
Cong Guan, Feng Chen, Ke Xue, Chunpeng Fan, Lichao Zhang, Ziqian Zhang, Pengyao Zhao, Zongzhang Zhang, Chao Qian, Lei Yuan, Yang Yu
- 22 Sept 2023 (modified: 25 Mar 2024)
- ICLR 2024 Conference Withdrawn Submission
- Readers: Everyone
Indeterminate Probability Theory
Tao Yang, Chuang Liu, Xiaofeng Ma, Weijia Lu, Ning Wu, Bingyang Li, ZHIFEI YANG, Peng Liu, Lin Sun, xiaodong Zhang, Can Zhang
- 22 Sept 2023 (modified: 11 Feb 2024)
- Submitted to ICLR 2024
- Readers: Everyone
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Jianming Pan, Xiao Yang, Weidong Ma, Weiqing Liu, Lewen Wang, Jiang Bian
- 22 Sept 2023 (modified: 25 Mar 2024)
- ICLR 2024 Conference Withdrawn Submission
- Readers: Everyone
DiffSDS: A geometric sequence diffusion model for protein backbone inpainting
Zhangyang Gao, Cheng Tan, Lirong Wu, Yufei Huang, Bozhen Hu, Stan Z. Li
- 22 Sept 2023 (modified: 25 Mar 2024)
- ICLR 2024 Conference Withdrawn Submission
- Readers: Everyone
Aligning Large Multimodal Models with Factually Augmented RLHF
Zhiqing Sun, Sheng Shen, Shengcao Cao, Haotian Liu, Chunyuan Li, Yikang Shen, Chuang Gan, Liangyan Gui, Yu-Xiong Wang, Yiming Yang, Kurt Keutzer, Trevor Darrell
- 22 Sept 2023 (modified: 11 Feb 2024)
- Submitted to ICLR 2024
- Readers: Everyone
TimelyGPT: Recurrent Convolutional Transformer for Long Time-series Representation
Ziyang Song, Qincheng Lu, Hao Xu, Yue Li
- 22 Sept 2023 (modified: 11 Feb 2024)
- Submitted to ICLR 2024
- Readers: Everyone