3 papers
cs.CL2026
Factual and Edit-Sensitive Graph-to-Sequence Generation via Graph-Aware Adaptive Noising
Aditya Hemant Shahane, Anuj Kumar Sirohi, Tanmoy Chakraborty +2
Fine-tuned autoregressive models for graph-to-sequence generation (G2S) often struggle with factual grounding and edit sensitivity. To tackle these issues, we propose a non-autoreg…
cs.CL2026
BiMol-Diff: A Unified Diffusion Framework for Molecular Generation and Captioning
Aditya Hemant Shahane, Anuj Kumar Sirohi, Devansh Arora +3
Bridging molecular structures and natural language is essential for controllable design. Autoregressive models struggle with long-range dependencies, while standard diffusion proce…
cs.AI2025
GOTHAM: Graph Class Incremental Learning Framework under Weak Supervision
Aditya Hemant Shahane, Prathosh A. P, Sandeep Kumar
Graphs are growing rapidly, along with the number of distinct label categories associated with them. Applications like e-commerce, healthcare, recommendation systems, and various s…