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Pan Li

73 papers · 2017–2026 · 12 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (8) 🌍 Conference Polyglot (12) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (13) 🏠 Conference Loyalist (21) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (11) πŸ† Keyword Champion (2) πŸ’Ž Century Club (71) πŸ—ƒοΈ Keyword Collector (256) πŸ“ˆ Trend Setter ⚑ Prolific Year (7) ❓ The Questioner (3) πŸ”₯ Unstoppable (9)

Conferences

NIPS (21) ICLR (15) ICML (9) EMNLP (8) IJCAI (4) AAAI (3) ACML (3) ICCV (3) AISTATS (2) CVPR (2) JMLR (2) IJCNLP (1)

Top co-authors

Olgica Milenkovic (9) Eli Chien (8) Muhan Zhang (6) Rongzhe Wei (5) Siqi Miao (5) Shaogang Gong (4) Zhangyang Wang (4) Runchao Li (4) Xianxuan Long (4) Yao Fu (4)

Research topics

Differential Privacy (2) Science (1) Privacy (1) Probability (1)

Keywords

graph neural network (11) representation learning (6) differential privacy (5) combinatorial optimization (3) link prediction (3) convex optimization (3) distribution shift (3) few-shot learning (3) submodular function minimization (3) hypergraph clustering (3) domain generalization (3) community detection (2) unsupervised learning (2) machine unlearning (2) submodular optimization (2) mutual information (2) self-supervised learning (2) model compression (2) information bottleneck (2) personalized generation (2)

Papers

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