2025
DecisionFlow: Advancing Large Language Model as Principled Decision Maker.
CoRR, May, 2025
Graph Foundation Models: A Comprehensive Survey.
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CoRR, May, 2025
ModelingAgent: Bridging LLMs and Mathematical Modeling for Real-World Challenges.
CoRR, May, 2025
RM-R1: Reward Modeling as Reasoning.
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CoRR, May, 2025
A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directions.
CoRR, April, 2025
OTC: Optimal Tool Calls via Reinforcement Learning.
CoRR, April, 2025
ToolRL: Reward is All Tool Learning Needs.
CoRR, April, 2025
Beyond Sample-Level Feedback: Using Reference-Level Feedback to Guide Data Synthesis.
CoRR, February, 2025
Internal Activation as the Polar Star for Steering Unsafe LLM Behavior.
CoRR, February, 2025
Towards LifeSpan Cognitive Systems.
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Trans. Mach. Learn. Res., 2025
Chain-of-Factors Paper-Reviewer Matching.
Proceedings of the ACM on Web Conference 2025, 2025
Beyond Answers: Transferring Reasoning Capabilities to Smaller LLMs Using Multi-Teacher Knowledge Distillation.
Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025
Semi-supervised Fine-tuning for Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025
Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Large Scale Knowledge Washing.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Self-Updatable Large Language Models by Integrating Context into Model Parameters.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
EscapeBench: Towards Advancing Creative Intelligence of Language Model Agents.
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Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
SMART: Self-Aware Agent for Tool Overuse Mitigation.
Proceedings of the Findings of the Association for Computational Linguistics, 2025
2024
One Step towards Autonomous AI Agent: Reasoning, Alignment and Planning
PhD thesis, 2024
Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting.
IEEE Trans. Knowl. Data Eng., 2024
EscapeBench: Pushing Language Models to Think Outside the Box.
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CoRR, 2024
PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making.
CoRR, 2024
SemiEvol: Semi-supervised Fine-tuning for LLM Adaptation.
CoRR, 2024
Self-Updatable Large Language Models with Parameter Integration.
CoRR, 2024
Strategist: Learning Strategic Skills by LLMs via Bi-Level Tree Search.
CoRR, 2024
Bridging Language and Items for Retrieval and Recommendation.
CoRR, 2024
MEMORYLLM: Towards Self-Updatable Large Language Models.
CoRR, 2024
TinyLLM: Learning a Small Student from Multiple Large Language Models.
CoRR, 2024
TPD: Enhancing Student Language Model Reasoning via Principle Discovery and Guidance.
CoRR, 2024
IterAlign: Iterative Constitutional Alignment of Large Language Models.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024
MEMORYLLM: Towards Self-Updatable Large Language Models.
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Proceedings of the Forty-first International Conference on Machine Learning, 2024
Language Models as Semantic Indexers.
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Proceedings of the Forty-first International Conference on Machine Learning, 2024
Data Science Tasks Implemented with Scripts versus GUI-Based Workflows: The Good, the Bad, and the Ugly.
Proceedings of the 40th International Conference on Data Engineering, ICDE 2024, 2024
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
PlayBest: Professional Basketball Player Behavior Synthesis via Planning with Diffusion.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
MinPrompt: Graph-based Minimal Prompt Data Augmentation for Few-shot Question Answering.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
2023
A Multi-View Multi-Task Learning Framework for Multi-Variate Time Series Forecasting.
IEEE Trans. Knowl. Data Eng., August, 2023
"Why Should I Review This Paper?" Unifying Semantic, Topic, and Citation Factors for Paper-Reviewer Matching.
CoRR, 2023
Professional Basketball Player Behavior Synthesis via Planning with Diffusion.
CoRR, 2023
Learning Structured Components: Towards Modular and Interpretable Multivariate Time Series Forecasting.
CoRR, 2023
Gotta: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023
Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
2022
MotifClass: Weakly Supervised Text Classification with Higher-order Metadata Information.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022
Scalable Graph Representation Learning via Locality-Sensitive Hashing.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
ReLiable: Offline Reinforcement Learning for Tactical Strategies in Professional Basketball Games.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
2021
The Pulse of Urban Transport: Exploring the Co-evolving Pattern for Spatio-temporal Forecasting.
ACM Trans. Knowl. Discov. Data, 2021
Hierarchical Metadata-Aware Document Categorization under Weak Supervision.
Proceedings of the WSDM '21, 2021
ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Evaluating Audience Loyalty and Authenticity in Influencer Marketing via Multi-task Multi-relational Learning.
Proceedings of the Fifteenth International AAAI Conference on Web and Social Media, 2021
#StayHome or #Marathon?: Social Media Enhanced Pandemic Surveillance on Spatial-temporal Dynamic Graphs.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021
2020
Few-Shot Learning for New User Recommendation in Location-based Social Networks.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020
2018
TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Doc2Cube: Allocating Documents to Text Cube Without Labeled Data.
Proceedings of the IEEE International Conference on Data Mining, 2018
ATRank: An Attention-Based User Behavior Modeling Framework for Recommendation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018