Poster Papers

Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging

Junkang Liu, Yuanyuan Liu, Fanhua Shang et al.

Improving Generalization of Neural Combinatorial Optimization for Vehicle Routing Problems via Test-Time Projection Learning

Yuanyao Chen, Rongsheng Chen, Fu Luo et al.

Improving Generalization with Flat Hilbert Bayesian Inference

Tuan Truong, Quyen Tran, Ngoc Quan Pham et al.

Improving Graph Neural Networks by Learning Continuous Edge Directions

Seong Ho Pahng, Sahand Hormoz

Improving Instruction-Following in Language Models through Activation Steering

Alessandro Stolfo, Vidhisha Balachandran, Safoora Yousefi et al.

Improving Language Model Distillation through Hidden State Matching

Sayantan Dasgupta, Trevor Cohn

Improving Large Language Model Planning with Action Sequence Similarity

Xinran Zhao, Hanie Sedghi, Bernd Bohnet et al.

Improving Large Vision and Language Models by Learning from a Panel of Peers

Jefferson Hernandez, Jing Shi, Simon Jenni et al.

Improving LLM Safety Alignment with Dual-Objective Optimization

Xuandong Zhao, Will Cai, Tianneng Shi et al.

Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens

Ting-Ji Huang, Jia-Qi Yang, Chunxu Shen et al.

Improving Long-Text Alignment for Text-to-Image Diffusion Models

Luping Liu, Chao Du, Tianyu Pang et al.

Improving Memory Efficiency for Training KANs via Meta Learning

Zhangchi Zhao, Jun Shu, Deyu Meng et al.

Improving Model Alignment Through Collective Intelligence of Open-Source Models

Junlin Wang, Roy Xie, Shang Zhu et al.

Improving Model-Based Reinforcement Learning by Converging to Flatter Minima

Shrinivas Ramasubramanian, Benjamin Freed, Alexandre Capone et al.

Improving Model Representation and Reducing KV Cache via Skip Connections with First Value Heads

Zhoutong Wu, Yuan Zhang, Yiming Dong et al.

Improving Monte Carlo Tree Search for Symbolic Regression

Zhengyao Huang, Daniel Huang, Tiannan Xiao et al.

Improving Multi-Class Calibration through Normalization-Aware Isotonic Techniques

Alon Arad, Saharon Rosset

Improving Multimodal Learning Balance and Sufficiency through Data Remixing

Xiaoyu Ma, Hao Chen, Yongjian Deng

Improving Multimodal Learning via Imbalanced Learning

Shicai Wei, Chunbo Luo, Yang Luo

Improving Neural Network Accuracy by Concurrently Training with a Twin Network

Benjamin Vandersmissen, Lucas Deckers, Jose Oramas

Improving Neural Optimal Transport via Displacement Interpolation

Jaemoo Choi, Yongxin Chen, Jaewoong Choi

Improving Noise Efficiency in Privacy-preserving Dataset Distillation

Runkai Zheng, Vishnu Dasu, Yinong Wang et al.

Improving Out-of-Distribution Detection via Dynamic Covariance Calibration

Kaiyu Guo, Zijian Wang, Tan Pan et al.

Improving Out-of-Distribution Detection with Markov Logic Networks

Konstantin Kirchheim, Frank Ortmeier

Improving Parallel Program Performance with LLM Optimizers via Agent-System Interfaces

Anjiang Wei, Allen Nie, Thiago Teixeira et al.

Improving Pretraining Data Using Perplexity Correlations

Tristan Thrush, Christopher Potts, Tatsunori Hashimoto

Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching

Zijing Ou, Mingtian Zhang, Andi Zhang et al.

Improving Progressive Generation with Decomposable Flow Matching

Moayed Haji-Ali, Willi Menapace, Ivan Skorokhodov et al.

Improving Rationality in the Reasoning Process of Language Models through Self-playing Game

Pinzheng Wang, Juntao Li, Zecheng Tang et al.

Improving Reasoning Performance in Large Language Models via Representation Engineering

Bertram Højer, Oliver Jarvis, Stefan Heinrich

Improving Rectified Flow with Boundary Conditions

Xixi Hu, Runlong Liao, Bo Liu et al.

Improving Regret Approximation for Unsupervised Dynamic Environment Generation

Harry Mead, Bruno Lacerda, Jakob Foerster et al.

Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning

Yiqun Chen, Lingyong Yan, Weiwei Sun et al.

Improving Reward Model Generalization from Adversarial Process Enhanced Preferences

Zhilong Zhang, Tian Xu, Xinghao Du et al.

Improving Reward Models with Proximal Policy Exploration for Preference-Based Reinforcement Learning

Yiwen Zhu, Jinyi Liu, Pengjie Gu et al.

Improving SAM for Camouflaged Object Detection via Dual Stream Adapters

Jiaming Liu, Linghe Kong, Guihai Chen

Improving Semantic Understanding in Speech Language Models via Brain-tuning

Omer Moussa, Dietrich Klakow, Mariya Toneva

Improving Semi-Supervised Semantic Segmentation with Sliced-Wasserstein Feature Alignment and Uniformity

Chen Yi Lu, Kasra Derakhshandeh, Somali Chaterji

Improving Soft Unification with Knowledge Graph Embedding Methods

Xuanming Cui, Chionh Peng, Adriel Kuek et al.

Improving Sound Source Localization with Joint Slot Attention on Image and Audio

Inho Kim, YOUNGKIL SONG, Jicheol Park et al.

Improving Task-Specific Multimodal Sentiment Analysis with General MLLMs via Prompting

Haoyu Zhang, Yinan Zhang, Chaolong Ying et al.

Improving Text-to-Image Consistency via Automatic Prompt Optimization

Melissa Hall, Michal Drozdzal, Oscar Mañas et al.

Improving the Continuity of Goal-Achievement Ability via Policy Self-Regularization for Goal-Conditioned Reinforcement Learning

Xudong Gong, Sen Yang, Feng Dawei et al.

Improving the Diffusability of Autoencoders

Ivan Skorokhodov, Sharath Girish, Benran Hu et al.

Improving the Effective Receptive Field of Message-Passing Neural Networks

Shahaf E. Finder, Ron Shapira Weber, Moshe Eliasof et al.

Improving the Euclidean Diffusion Generation of Manifold Data by Mitigating Score Function Singularity

Zichen Liu, Wei Zhang, Tiejun Li

Improving the Generation and Evaluation of Synthetic Data for Downstream Medical Causal Inference

Harry Amad, Zhaozhi Qian, Dennis Frauen et al.

Improving the Sparse Structure Learning of Spiking Neural Networks from the View of Compression Efficiency

Jiangrong Shen, Qi Xu, Gang Pan et al.

Improving the Statistical Efficiency of Cross-Conformal Prediction

Improving the Straight-Through Estimator with Zeroth-Order Information

Ningfeng Yang, Tor Aamodt