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Amit S

2 accepted papers

2025

MOGIC: Metadata-infused Oracle Guidance for Improved Extreme Classification

ICML 2025poster

Retrieval-augmented classification and generation models benefit from *early-stage fusion* of high-quality text-based metadata, often called memory, but face high latency and noise sensitivity. In extreme classification (XC), where low latency is crucial, existing methods use *late-stage fusion* for…

2021

GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph

NeurIPS 2021poster

The representation learning on textual graph is to generate low-dimensional embeddings for the nodes based on the individual textual features and the neighbourhood information. Recent breakthroughs on pretrained language models and graph neural networks push forward the development of corresponding…