How Expressive are Knowledge Graph Foundation Models? Permalink
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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.
Portfolio
Research Internships at Eigent-AI & CAMEL-AI
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Worked on multi-agent systems and data generation for verifiable RL.
HTP Accepted to ACL 2026 (Oral)
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Our paper “Hierarchical Token Prepending: Enhancing Information Flow in Decoder-based LLM Embeddings” has been accepted to ACL 2026 (Oral).
TDA Accepted to ACL 2026
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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.
Workshop Proposal Accepted at ICML 2026
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Our workshop proposal, “Graph Foundation Models: A New Era for Graph Machine Learning,” has been accepted for ICML 2026!
Selected as Top Reviewer for NeurIPS 2025
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Honored to be recognized as a Top Reviewer at NeurIPS 2025.
Research Intern at Snap Inc. (User Modelling & Personalization)
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Research intern at Snap Inc., User Modelling and Personalization teams.
Organizing the SEA Workshop @ NeurIPS 2025
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Co-organizing the Scaling Environments for Agents (SEA) Workshop at NeurIPS 2025.