Papers by Abhishek Pandey
A Survey of Large Language Models for Text-Guided Molecular Discovery: From Molecule Generation to Optimization (2026.acl-long)
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| Challenge: | Large language models (LLMs) are introducing a paradigm shift in molecular discovery by enabling text-guided interaction with chemical spaces through natural language and symbolic notations. |
| Approach: | They analyze the current LLM learning paradigms to tackle four critical evaluation dimensions that have emerged as critical dimensions in recent studies. |
| Outcome: | The proposed models are able to interact with chemical spaces through natural language and symbolic notations, and have emerging extensions to incorporate multi-modal inputs. |
MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization (2026.acl-long)
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| Challenge: | Existing methods for molecular optimization use expensive oracle evaluations to achieve sample efficiency under limited oracular budget. |
| Approach: | They propose a framework that iteratively refines a lead compound to improve molecular properties while preserving structural similarity to the original molecule. |
| Outcome: | The proposed framework achieves 90% success on single-property tasks and 52% on multi-propety task using only 500 oracle calls. |