Papers
TMAE:Learning Targeted Multi-Agent Exploration via Causal Inference
Chuxiong Sun, Dunqi Yao, Rui Wang et al.
M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference
Chuxiong Sun, Peng He, Qirui Ji et al.
DWTSG: Parameter-Efficient Fine-Tuning of Large Pre-trained Models via Discrete Wavelet Transform and Subband Guidance
Chengwei Sun, Jiwei Wei, Shiyuan He et al.
Complex Instruction Following with Diverse Style Policies in Football Games
Chenglu Sun, Shuo Shen, Haonan Hu et al.
Counterfactual Fairness with Imperfect Causal Graphs
Cong Su, Qiaoyu Tan, Carlotta Domeniconi et al.
Ambiguity-Tolerant Cross-Modal Hashing with Partial Labels
Chao Su, Yanan Li, Xu Wang et al.
Planning in Branch-and-Bound: Model-Based Reinforcement Learning for Exact Combinatorial Optimization
Paul Strang, Zacharie Alès, Côme Bissuel et al.
Improving Stochastic Action-Constrained Reinforcement Learning via Truncated Distributions
Roland Stolz, Michael Eichelbeck, Matthias Althoff
Learning from Reasoning Failures via Synthetic Data Generation
Gabriela Ben Melech Stan, Estelle Aflalo, Avinash Madasu et al.
Scaling Laws for Conditional Emergence of Multilingual Image Captioning via Generalization from Translation
Julian Spravil, Sebastian Houben, Sven Behnke
Formal Abductive Latent Explanations for Prototype-Based Networks
Jules Soria, Zakaria Chihani, Julien Girard-Satabin et al.
Learning the Latent Structure: A Feature-Centric Approach to Graph Data Augmentation
Yu Song, Zhigang Hua, Yan Xie et al.
COGS: A Causal Representation Learning Framework for Out-of-Distribution Generalization in Time Series
Xinxin Song, Yuxiao Cheng, Tingxiong Xiao et al.
Privacy on the Fly: A Predictive Adversarial Transformation Network for Mobile Sensor Data
Tianle Song, Chenhao Lin, Yang Cao et al.
Leveraging Image as Compressed Visual Prompt and Hierarchical Visual Knowledge for Effective Image Utilization in MLLMs
Shezheng Song, Kangcheng Ding, Shan Zhao et al.
Synthetic Forgetting Without Access: A Few-Shot Zero-Glance Framework for Machine Unlearning
Qipeng Song, Nan Yang, Ziqi Xu et al.
KSS-MoE: Knowledge Space Synergy Framework in Mixture of Experts for Continual Visual Instruction Tuning
Lingyun Song, Ziyao Chen, Kang Pan et al.
Breaking One-Size-Fits-All: Revisiting Out-of-Distribution Detection on Graphs Under Diverse Distribution Shifts
Chuancheng Song, Hanyang Shen, Yan Dong et al.
Injection, Attack and Erasure: Revocable Backdoor Attacks via Machine Unlearning
Baogang Song, Dongdong Zhao, Jianwen Xiang et al.
Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry
Vladimir Solodkin, Andrey Veprikov, Alexander Chernyavskiy et al.
MultiTab: A Scalable Foundation for Multitask Learning on Tabular Data
Dimitrios Sinodinos, Jack Yi Wei, Narges Armanfard
Leap of FAITH from GNN-to-MLP: Fairness Aware Inference via DisTillation of GrapH Knowledge
Vipul Kumar Singh, Jyotismita Barman, Sandeep Kumar et al.
CRISP: Curriculum-Inducing Primitive Informed Subgoal Prediction for Boosting Hierarchical Reinforcement Learning
Utsav Singh, Vinay P. Namboodiri
Learning to Collaborate: An Orchestrated-Decentralized Framework for Peer-to-Peer LLM Federation
Inderjeet Singh, Eleonore Vissol-Gaudin, Andikan Otung et al.
Graph Flow Matching: Enhancing Image Generation with Neighbor-Aware Flow Fields
Md Shahriar Rahim Siddiqui, Moshe Eliasof, Eldad Haber