Derek Lim

38 papers A* 15A 2Journal 20Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Any-Subgroup Equivariant Networks via Symmetry Breaking.
CoRR
Abhinav Goel, Derek Lim, Hannah Lawrence, Stefanie Jegelka, Ningyuan Huang
2026 A* conf
Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions.
AAAI
Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron
2025 J jnl
Learning on LLM Output Signatures for gray-box LLM Behavior Analysis.
CoRR
Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron
2024 A* conf
A Canonicalization Perspective on Invariant and Equivariant Learning.
NeurIPS
George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang
2024 J jnl
A Canonization Perspective on Invariant and Equivariant Learning.
CoRR
George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang
2024 J jnl
Future Directions in Foundations of Graph Machine Learning.
CoRR
Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024 A* conf
Graph Metanetworks for Processing Diverse Neural Architectures.
ICLR
Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
2024 J jnl
Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models.
CoRR
Moe Putterman, Derek Lim, Yoav Gelberg, Stefanie Jegelka, Haggai Maron
2024 A* conf
Position: Future Directions in the Theory of Graph Machine Learning.
ICML
Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024 A* conf
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning.
ICLR
Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka
2024 A* conf
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof.
NeurIPS
Derek Lim, Theo Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka
2024 J jnl
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof.
CoRR
Derek Lim, Moe Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka
2023 A* conf
Equivariant Polynomials for Graph Neural Networks.
ICML
Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman
2023 J jnl
Equivariant Polynomials for Graph Neural Networks.
CoRR
Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman
2023 A* conf
Expressive Sign Equivariant Networks for Spectral Geometric Learning.
NeurIPS
Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
2023 J jnl
Expressive Sign Equivariant Networks for Spectral Geometric Learning.
CoRR
Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
2023 A* conf
Graph Inductive Biases in Transformers without Message Passing.
ICML
Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim
2023 J jnl
Graph Inductive Biases in Transformers without Message Passing.
CoRR
Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim
2023 J jnl
Graph Metanetworks for Processing Diverse Neural Architectures.
CoRR
Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
2023 A* conf
Sign and Basis Invariant Networks for Spectral Graph Representation Learning.
ICLR
Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
2023 J jnl
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning.
CoRR
Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka
2023 A conf
The Power of Recursion in Graph Neural Networks for Counting Substructures.
AISTATS
Behrooz Tahmasebi, Derek Lim, Stefanie Jegelka
2022 A* conf
Equivariant Subgraph Aggregation Networks.
ICLR
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
2022 J jnl
Sign and Basis Invariant Networks for Spectral Graph Representation Learning.
CoRR
Derek Lim, Joshua Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
2022 J jnl
The Doubly Stochastic Single Eigenvalue Problem: A Computational Approach.
Exp. Math.
Amit Harlev, Charles R. Johnson, Derek Lim
2022 — conf
The First Learning on Graphs Conference: Preface.
LoG
Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov
2022 A* conf
Understanding Doubly Stochastic Clustering.
ICML
Tianjiao Ding, Derek Lim, René Vidal, Benjamin D. Haeffele
2021 A* conf
Equivariant Manifold Flows.
NeurIPS
Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2021 J jnl
Equivariant Manifold Flows.
CoRR
Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2021 J jnl
Equivariant Subgraph Aggregation Networks.
CoRR
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
2021 A conf
Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform.
ICWSM
Derek Lim, Austin R. Benson
2021 A* conf
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods.
NeurIPS
Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim
2021 J jnl
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods.
CoRR
Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim
2021 J jnl
New Benchmarks for Learning on Non-Homophilous Graphs.
CoRR
Derek Lim, Xiuyu Li, Felix Hohne, Ser-Nam Lim
2020 J jnl
Doubly Stochastic Subspace Clustering.
CoRR
Derek Lim, René Vidal, Benjamin D. Haeffele
2020 J jnl
Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform.
CoRR
Derek Lim, Austin R. Benson
2020 A* conf
Neural Manifold Ordinary Differential Equations.
NeurIPS
Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2020 J jnl
Neural Manifold Ordinary Differential Equations.
CoRR
Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa