Research

* Equal contributions.

• CausalBind: Causal Concept Alignment for Protein-Ligand Virtual Screening
  Loka Li, Jin Tian, Kun Zhang.
  International Conference on Learning Representations (ICLR) workshop on Generative and Experimental Perspectives for Biomolecular Design, 2026.

• PersonaX: Multimodal Datasets with LLM-Inferred Behavior Traits
  Loka Li*, Wong Yu Kang*, Minghao Fu, Guangyi Chen, Zhenhao Chen, Gongxu Luo, Yuewen Sun, Salman Khan, Peter Spirtes, Kun Zhang.
  International Conference on Learning Representations (ICLR), 2026.

• Characterization and Learning of Causal Graphs with Latent Confounders and Post-treatment Selection from Interventional Data
  Gongxu Luo, Loka Li, Guangyi Chen, Haoyue Dai, Kun Zhang.
  International Conference on Learning Representations (ICLR), 2026.

• How Effective is Your Rebuttal? Identifying Causal Models from the OpenReview System
  Loka Li*, Ibrahim Aldarmaki*, Minghao Fu, Wong Yu Kang, Yunlong Deng, Qiang Huang, Jing Yang, Jin Tian, Guangyi Chen, Kun Zhang.
  Neural Information Processing Systems (NeurIPS) Workshop on CauScien: Uncovering Causality in Science, 2025.

• MemR3: Memory Retrieval via Reflective Reasoning for LLM Agents
  Xingbo Du, Loka Li, Duzhen Zhang, Le Song.
  arXiv, 2025.

• Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders
  Gongxu Luo, Haoyue Dai, Loka Li, Chengqian Gap, Boyang Sun, Kun Zhang.
  Neural Information Processing Systems (NeurIPS), 2025.
• ψDAG: Projected Stochastic Approximation Iteration for DAG Structure Learning
  Klea Ziu, Slavomír Hanzely, Loka Li, Kun Zhang, Martin Takáč, Dmitry Kamzolov
  arXiv, 2024.
• Reflection-Window Decoding: Text Generation with Selective Refinement
  Zeyu Tang, Zhenhao Chen, Xiangchen Song, Loka Li, Yunlong Deng, Yifan Shen, Guangyi Chen, Peter Spirtes, Kun Zhang.
  International Conference on Machine Learning (ICML), 2025.

• Causal Representation Learning from Multimodal Biological Observations
  Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang, Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, Eric Xing, Kun Zhang.
  International Conference on Learning Representations (ICLR), 2025.

• Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models
  Loka Li*, Zhenhao Chen*, Guangyi Chen*, Yixuan Zhang, Yusheng Su, Eric Xing, Kun Zhang.
  arXiv, 2024.

• On Causal Discovery in the Presence of Deterministic Relations
  Loka Li*, Haoyue Dai*, Hanin Ghothani, Biwei Huang, Jiji Zhang, Shahar Harel, Isaac Bentwich, Guangyi Chen, Kun Zhang.
  Neural Information Processing Systems (NeurIPS), 2024.

• Federated Causal Discovery from Heterogeneous Data
  Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang.
  International Conference on Learning Representations (ICLR), 2024.

• Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation Learning
  Loka Li, Siyuan Liang, Zihao Zhu, Chris Ding, Hongyuan Zha, Baoyuan Wu.
  AAAI Conference on Artificial Intelligence (AAAI), 2024.

Service

- Serving as a reviewer for conferences and journals, including:

• International Conference on Machine Learning (ICML), 2024-2026.
• Neural Information Processing Systems (NeurIPS), 2024-2025.
• International Conference on Learning Representations (ICLR), 2024-2026.
• Association for the Advancement of Artificial Intelligence Conference (AAAI), 2026.
• International Conference on Artificial Intelligence and Statistics (AISTATS), 2025-2026.
• International Conference on Data Mining (ICDM), 2024.
• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026.
• IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024.

- Serving as a teaching assistant for the courses, including:

• 2024/2025 Spring: ML808-Advanced Topics in Causality and Machine Learning. (Instructor: Prof. Jin Tian)
• 2024/2025 Fall: ML801-Foundations and Advanced Topics in Machine Learning. (Instructor: Prof. Tongliang Liu)
• 2023/2024 Spring: ML802-Advanced Machine Learning. (Instructor: Prof. Tongliang Liu)
• 2023/2024 Fall: ML803-Advanced Probabilistic and Statistical Inference. (Instructor: Prof. Kun Zhang)

Fun

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