Xiangchen Song
According to our database1,
Xiangchen Song authored at least 46 papers
between 2020 and 2026.
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Bibliography
2026
GRASP: Plan-Guided Graph Retrieval with Adaptive Fusion and Reranking on Semi-Structured Knowledge Bases.
CoRR, May, 2026
CausaLab: A Scalable Environment for Interactive Causal Discovery Toward AI Scientists.
CoRR, May, 2026
CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?
CoRR, May, 2026
MoRe: Modular Representations for Principled Continual Representation Learning on Sequential Data.
CoRR, May, 2026
Mechanistic Interpretability Should Prioritize Feature Consistency in Sparse Autoencoders.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026
2025
Beyond the Black Box: Identifiable Interpretation and Control in Generative Models via Causal Minimality.
CoRR, December, 2025
Parameter-Efficient Fine-Tuning with Differential Privacy for Robust Instruction Adaptation in Large Language Models.
CoRR, December, 2025
Multi-Scale Feature Fusion and Graph Neural Network Integration for Text Classification with Large Language Models.
CoRR, November, 2025
CoRR, October, 2025
Controllable Abstraction in Summary Generation for Large Language Models via Prompt Engineering.
CoRR, October, 2025
Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models.
CoRR, October, 2025
CoRR, October, 2025
Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs.
CoRR, May, 2025
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025
Proceedings of the Forty-second International Conference on Machine Learning, 2025
On the Identification of Temporal Causal Representation with Instantaneous Dependence.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
2024
On the Identification of Temporally Causal Representation with Instantaneous Dependence.
CoRR, 2024
A Randomized Controlled Trial on Anonymizing Reviewers to Each Other in Peer Review Discussions.
CoRR, 2024
When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting.
CoRR, 2024
Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models.
CoRR, 2024
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
IEEE Trans. Wirel. Commun., 2022
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks.
CoRR, 2022
TaxoEnrich: Self-Supervised Taxonomy Completion via Structure-Semantic Representations.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022
Learning Multi-granularity Consecutive User Intent Unit for Session-based Recommendation.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract).
Proceedings of the IEEE International Conference on Big Data, 2022
2021
Modeling Multi-granularity User Intent Evolving via Heterogeneous Graph Neural Networks for Session-based Recommendation.
CoRR, 2021
Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Recommendation.
CoRR, 2021
Who Should Go First? A Self-Supervised Concept Sorting Model for Improving Taxonomy Expansion.
CoRR, 2021
BiTe-GCN: A New GCN Architecture via Bidirectional Convolution of Topology and Features on Text-Rich Networks.
Proceedings of the WSDM '21, 2021
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations, 2021
ChemNER: Fine-Grained Chemistry Named Entity Recognition with Ontology-Guided Distant Supervision.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
BiTe-GCN: A New GCN Architecture via BidirectionalConvolution of Topology and Features on Text-Rich Networks.
CoRR, 2020
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation.
CoRR, 2020
CoRR, 2020
Fine-Grained Named Entity Recognition with Distant Supervision in COVID-19 Literature.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020