A Theory of Link Prediction Accepted to NeurIPS 2023
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Our paper “A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs” was accepted to NeurIPS 2023.
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Our paper “A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs” was accepted to NeurIPS 2023.
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Our paper “Link Prediction with Relational Hypergraphs” is now available on arXiv.
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Our paper “A Novel Multiobjective Genetic Programming Approach to High-Dimensional Data Classification” was accepted to IEEE Transactions on Cybernetics.
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Our paper “Cooperative Graph Neural Networks” was accepted to ICML 2024.
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Our paper “One Model, Any Conjunctive Query: Graph Neural Networks for Answering Complex Queries over Knowledge Graphs” is now available on arXiv.
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Our paper “Theoretical Insights into Line Graph Transformation on Graph Learning” was accepted to the NeurIPS 2024 Workshop of Symmetry and Geometry in Neural Representations.
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Our paper ‘How Expressive are Knowledge Graph Foundation Models?’ is now available on arXiv. Check it out for a detailed analysis of the expressive power of KGFMs.
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Worked on multi-agent systems and data generation for verifiable RL.
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Honored to be recognized as a Top Reviewer at NeurIPS 2025.
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Our paper “Hierarchical Token Prepending: Enhancing Information Flow in Decoder-based LLM Embeddings” has been accepted to ACL 2026 (Oral).
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Our paper “Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling” has been accepted to ACL 2026.
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Our workshop proposal, “Graph Foundation Models: A New Era for Graph Machine Learning,” has been accepted for ICML 2026!
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Honored to be recognized as an ICML 2026 Silver Reviewer.
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Research intern at Snap Inc., User Modelling and Personalization teams.
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Co-organizing the Scaling Environments for Agents (SEA) Workshop at NeurIPS 2025.
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Our paper “RelAgent: LLM Agents as Data Scientists for Relational Learning” is now available on arXiv.