News

[June 2025] Selected again as one of the top 10% of reviewers for KDD 2025 (February cycle).

[Apr 2025] Our paper on A Mechanistic View of How Post-Training Reshapes LLMs has won the NENLP 2025 Outstanding Paper Award. [PDF][slides]

[Apr 2025] Our paper on A Mechanistic View of How Post-Training Reshapes LLMs has been selected as Oral presentation for NENLP 2025.

[Apr 2025] Gave a talk on AI Interpretability at Georgia Institute of Technology.

[Apr 2025] Gave a talk on AI Interpretability at Emory University.

[Feb 2025] Serving as an Area Chair for ACL ARR 2025.

[Feb 2025] Our paper on unified attribution in explainable AI, data-centric AI, and mechanistic interpretability is on arXiv now. [PDF]

[Dec 2024] Selected as one of the top 10% of reviewers for KDD 2025.

[Nov 2024] Our paper on LLM-based explainable molecular concept learning is accepted by COLING 2025. [PDF]

[Oct 2024] Our paper on explainable graph learning for predicting ICU length of stay is accepted by ISR. [PDF]

[Oct 2024] Our paper on generalized group data attribution is on arXiv now. [PDF]

[July 2024] A Mind Map of Knowledge in LLMs.

[June 2024] Our paper on controlling LLM behaviors with LLM itself as a judge is on arXiv now. [PDF] [Code] [website]

[May 2024] Defended my Ph.D. thesis “Explainable AI for Graph Data”.

[May 2024] Our paper on efficient ensembling for training data attribution is on arXiv now. [PDF]

[May 2024] Our paper on measure-theoretic compact fuzzy set representation for taxonomy expansion is accepted by ACL 2024 as Findings. [PDF]

[May 2024] Two papers on GNNs for explainable material science and benchmarking LLMs on scientific problems are accepted by ICML 2024. [PDF1] [PDF2]

[Feb 2024] Gave a talk on Explainable AI for Graph Data and More at the AI4LIFE Group at Harvard.

[Dec 2023] Our paper on LLM-based explainable molecular concept learning is accepted by the XAI4Sci workshop at AAAI 2024. [PDF]

[Dec 2023] Our paper on GNNs for explainable material science is accepted by the AI4Mat workshop at NeurIPS 2023. [PDF]

[Aug 2023] Certified Excellence in Reviewing for KDD 2023 (30 in 1551).

[July 2023] Selected as one of the 2023 Amazon Fellows.

[July 2023] Received the J.P. Morgan Chase AI Ph.D. Fellowship.

[July 2023] Gave a talk on the PaGE-Link paper at Amazon Trans.AI Research Talk Series. [slides]

[June 2023] Our survey paper on GNN acceleration is on arXiv now, which covers algorithms, systems, and customized hardware. [PDF]

[Apr 2023] One paper on GNN distillation for link prediction is accepted by ICML 2023. [PDF]

[Feb 2023] Gave a talk on the GStarX paper at AI TIME NeurIPS Talk Series. [slides][video (in Chinese, starting from 00:19:05)]

[Jan 2023] One paper on GNN explanation for link prediction is accepted by WWW 2023. [PDF]

[Sept 2022] One paper on GNN explanation is accepted by NeurIPS 2022. [PDF]

[July 2022] Selected as one of the top 10% of reviewers for ICML 2022.

[Apr 2022] A draft chapter of A Trip from Machine Learning to Measure and Probability.

[Jan 2022] Two papers on graph distillation and graph condensation are accepted by ICLR 2022. [PDF1] [PDF2]

[Nov 2021] The first draft of Explainability Mind Map.

[Nov 2019] First launch of my website.