Furui Liu

18 papers · 2021–2026 · 7 conferences · across top CS/AI conferences

Achievements

+7 more ↓

🐝 Cross-Pollinator (3) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🏃 Academic Marathon (5)

🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) ⚡ Prolific Year (8) ❓ The Questioner 🗃️ Keyword Collector (93) 💎 Century Club (16)

Conferences

AAAI (6) NIPS (4) CVPR (2) ICCV (2) ICML (2) ACL (1) JMLR (1)

Top co-authors

Guangyong Chen (5) Pheng-Ann Heng (4) Kun Kuang (4) Fei Wu (3) Yiming Wang (3) Leong Hou U (3) Jianye Hao (2) Kaiyan Zhao (2) Jiaze Wang (2) Xinwei Shen (2)

Research topics

Machine Learning (1) Privacy (1)

Keywords

causal inference (7) disentangled representation (2) exploration bonus (2) backdoor confounding (2) bisimulation metric (2) semi-supervised learning (2) structural causal model (2) intrinsic reward (2) credit assignment (2) evidential deep learning (2) multi-agent reinforcement learning (2) state discrepancy (2) reinforcement learning (2) autonomous driving (1) weakly supervised learning (1) medical imaging (1) uncertainty quantification (1) metric learning (1) policy gradient (1) deep learning (1)

Papers

AIPO: Adaptive Information Guided Token-Level Reinforcement Learning for Large Language Model Reasoning ACL 2026 DSAP: Enhancing Generalization in Goal-Conditioned Reinforcement Learning AAAI 2026 ANEDL: Adaptive Negative Evidential Deep Learning for Open-Set Semi-supervised Learning AAAI 2024 Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus NIPS 2024 Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples AAAI 2024 DR-Label: Label Deconstruction and Reconstruction of GNN Models for Catalysis Systems AAAI 2024 Traj-MAE: Masked Autoencoders for Trajectory Prediction ICCV 2023 Uncertainty Estimation by Fisher Information-based Evidential Deep Learning ICML 2023 Efficient Potential-based Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric NIPS 2023 Invariant Learning via Probability of Sufficient and Necessary Causes NIPS 2023 Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation AAAI 2023 Learning from Good Trajectories in Offline Multi-Agent Reinforcement Learning AAAI 2023 RepMode: Learning to Re-Parameterize Diverse Experts for Subcellular Structure Prediction CVPR 2023 CauSSL: Causality-inspired Semi-supervised Learning for Medical Image Segmentation ICCV 2023 ConfounderGAN: Protecting Image Data Privacy with Causal Confounder NIPS 2022 Deconfounded Value Decomposition for Multi-Agent Reinforcement Learning ICML 2022 Weakly Supervised Disentangled Generative Causal Representation Learning JMLR 2022 CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models CVPR 2021