ICML 2024 Conference Submissions

Compressing Large Language Models by Joint Sparsification and Quantization
Jinyang Guo, Jianyu Wu, Zining Wang, Jiaheng Liu, Ge Yang, Yifu Ding, Ruihao Gong, Haotong Qin, Xianglong Liu
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency
HyeongJin Kim, Sangwon Kim, Dasom Ahn, Jong Taek Lee, Byoung Chul Ko
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Towards Unified Multi-granularity Text Detection with Interactive Attention
Xingyu Wan, Chengquan Zhang, Pengyuan Lyu, Sen Fan, Zihan Ni, Kun Yao, Errui Ding, Jingdong Wang
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Spotlight
- Readers: Everyone
Federated Self-Explaining GNNs with Anti-shortcut Augmentations
Linan Yue, Qi Liu, Weibo Gao, Ye Liu, Kai Zhang, Yichao Du, Li Wang, Fangzhou Yao
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach
Bin Zhang, Hangyu Mao, Lijuan Li, Zhiwei Xu, Dapeng Li, Rui Zhao, Guoliang Fan
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
Inwoo Hwang, Yunhyeok Kwak, Suhyung Choi, Byoung-Tak Zhang, Sanghack Lee
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
An Empirical Study Into What Matters for Calibrating Vision-Language Models
Weijie Tu, Weijian Deng, Dylan Campbell, Stephen Gould, Tom Gedeon
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis
Luyuan Xie, Manqing Lin, Tianyu Luan, Cong Li, Yuejian Fang, Qingni Shen, Zhonghai Wu
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Calibration Bottleneck: Over-compressed Representations are Less Calibratable
Deng-Bao Wang, Min-Ling Zhang
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming
Xinlei Niu, Christian Walder, Jing Zhang, Charles Patrick Martin
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Projecting Molecules into Synthesizable Chemical Spaces
Shitong Luo, Wenhao Gao, Zuofan Wu, Jian Peng, Connor W. Coley, Jianzhu Ma
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Position: Embracing Negative Results in Machine Learning
Florian Karl, Malte Kemeter, Gabriel Dax, Paulina Sierak
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Oral
- Readers: Everyone
Position: A Call to Action for a Human-Centered AutoML Paradigm
Marius Lindauer, Florian Karl, Anne Klier, Julia Moosbauer, Alexander Tornede, Andreas C Mueller, Frank Hutter, Matthias Feurer, Bernd Bischl
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Total Variation Distance Meets Probabilistic Inference
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
TVE: Learning Meta-attribution for Transferable Vision Explainer
Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
Le Yu, Bowen Yu, Haiyang Yu, Fei Huang, Yongbin Li
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Invariant Risk Minimization Is A Total Variation Model
Zhao-Rong Lai, Weiwen Wang
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
An Efficient Maximal Ancestral Graph Listing Algorithm
Tian-Zuo Wang, Wen-Bo Du, Zhi-Hua Zhou
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Spotlight
- Readers: Everyone
Generalizing Orthogonalization for Models with Non-Linearities
David Rügamer, Chris Kolb, Tobias Weber, Lucas Kook, Thomas Nagler
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
DetKDS: Knowledge Distillation Search for Object Detectors
Lujun Li, Yufan Bao, Peijie Dong, Chuanguang Yang, Anggeng Li, Wenhan Luo, Qifeng Liu, Wei Xue, Yike Guo
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
Dachun Kai, Jiayao Lu, Yueyi Zhang, Xiaoyan Sun
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Transolver: A Fast Transformer Solver for PDEs on General Geometries
Haixu Wu, Huakun Luo, Haowen Wang, Jianmin Wang, Mingsheng Long
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Spotlight
- Readers: Everyone
Why Larger Language Models Do In-context Learning Differently?
Zhenmei Shi, Junyi Wei, Zhuoyan Xu, Yingyu Liang
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
New Bounds on the Cohesion of Complete-link and Other Linkage Methods for Agglomerative Clustering
Sanjoy Dasgupta, Eduardo Sany Laber
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone
Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
Xutong Liu, Siwei Wang, Jinhang Zuo, Han Zhong, Xuchuang Wang, Zhiyong Wang, Shuai Li, Mohammad Hajiesmaili, John C.S. Lui, Wei Chen
- Published: 02 May 2024, Last Modified: 25 Jun 2024
- ICML 2024 Poster
- Readers: Everyone