Pan Li

AR-Nav Benchmark: Augmented Reality Navigation with Vision and Language AAAI 2026 Chain-of-Search: Parameter-Efficient Reasoning for Zero-Shot Object Navigation AAAI 2026 Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness ICLR 2025 FAEDKV: Infinite-Window Fourier Transform for Unbiased KV Cache Compression EMNLP 2025 Generalization Principles for Inference over Text-Attributed Graphs with Large Language Models ICML 2025 Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick JMLR 2025 LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation ICLR 2025 Optimal Distributed Training With Co-Adaptive Data Parallelism in Heterogeneous Environments IJCAI 2025 Pruning Weights but Not Truth: Safeguarding Truthfulness While Pruning LLMs EMNLP 2025 Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs EMNLP 2025 Rethinking Addressing in Language Models via Contextualized Equivariant Positional Encoding ICML 2025 Risk-Aware Task Migration for Multiplex Unmanned Swarm Networks in Adversarial Environments IJCAI 2025 Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation ICLR 2025 Towards Universal Debiasing for Language Models-based Tabular Data Generation EMNLP 2025 Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning ICML 2025 Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing ICLR 2025 What Are Good Positional Encodings for Directed Graphs? ICLR 2025 When Truthful Representations Flip Under Deceptive Instructions? EMNLP 2025 A Non-parametric Graph Clustering Framework for Multi-View Data AAAI 2024 Certified Machine Unlearning via Noisy Stochastic Gradient Descent NeurIPS 2024 Differentially Private Graph Diffusion with Applications in Personalized PageRanks NeurIPS 2024 GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts NeurIPS 2024 Graph As Point Set ICML 2024 Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning NeurIPS 2024 Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics ICML 2024 MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training NeurIPS 2024 On the Stability of Expressive Positional Encodings for Graphs ICLR 2024 Pairwise Alignment Improves Graph Domain Adaptation ICML 2024 Polynomial Width is Sufficient for Set Representation with High-dimensional Features ICLR 2024 Towards Poisoning Fair Representations ICLR 2024 Training Compute-Optimal Protein Language Models NeurIPS 2024 Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection NeurIPS 2023 Dual-Channel Span for Aspect Sentiment Triplet Extraction EMNLP 2023 Equivariant Hypergraph Diffusion Neural Operators ICLR 2023 Extensible and Efficient Proxy for Neural Architecture Search ICCV 2023 Interpretable Geometric Deep Learning via Learnable Randomness Injection ICLR 2023 Structural Re-weighting Improves Graph Domain Adaptation ICML 2023 Unsupervised Learning for Combinatorial Optimization Needs Meta Learning ICLR 2023 Better Trigger Inversion Optimization in Backdoor Scanning CVPR 2022 Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks ICLR 2022 Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction ICLR 2022 Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism ICML 2022 Ranking Distance Calibration for Cross-Domain Few-Shot Learning CVPR 2022 Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective NeurIPS 2022 Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation NeurIPS 2022 Adaptive Universal Generalized PageRank Graph Neural Network ICLR 2021 Adversarial Graph Augmentation to Improve Graph Contrastive Learning NeurIPS 2021 A Simple Feature Augmentation for Domain Generalization ICCV 2021 A Web Scale Entity Extraction System EMNLP 2021 Generic Neural Architecture Search via Regression NeurIPS 2021 Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks ICLR 2021 Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning NeurIPS 2021 Local Hyper-Flow Diffusion NeurIPS 2021 Nested Graph Neural Networks NeurIPS 2021 Regularising Knowledge Transfer by Meta Functional Learning IJCAI 2021 Striking a Balance Between Stability and Plasticity for Class-Incremental Learning ICCV 2021 Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning NeurIPS 2020 Graph Information Bottleneck NeurIPS 2020 Quadratic Decomposable Submodular Function Minimization: Theory and Practice JMLR 2020 HS^2: Active learning over hypergraphs with pointwise and pairwise queries AISTATS 2019 Conditional Structure Generation through Graph Variational Generative Adversarial Nets NeurIPS 2019 Differentially Private Community Detection in Attributed Social Networks ACML 2019 Learning to Learn Gradient Aggregation by Gradient Descent IJCAI 2019 Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection NeurIPS 2019 Towards Controllable and Personalized Review Generation EMNLP 2019 Multidimensional Time Series Anomaly Detection: A GRU-based Gaussian Mixture Variational Autoencoder Approach ACML 2018 Quadratic Decomposable Submodular Function Minimization NeurIPS 2018 Revisiting Decomposable Submodular Function Minimization with Incidence Relations NeurIPS 2018 SecureNets: Secure Inference of Deep Neural Networks on an Untrusted Cloud ACML 2018 Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering ICML 2018 Efficient Rank Aggregation via Lehmer Codes AISTATS 2017 Inhomogeneous Hypergraph Clustering with Applications NeurIPS 2017