Papers by Aniketh Garikaparthi
MIR: Methodology Inspiration Retrieval for Scientific Research Problems (2025.acl-long)
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Aniketh Garikaparthi, Manasi Patwardhan, Aditya Sanjiv Kanade, Aman Hassan, Lovekesh Vig, Arman Cohan
| Challenge: | Existing methods for generating ideas rely on grounding the discovery process within the literature, but their effectiveness varies significantly with the quality and nature of the retrieved literature. |
| Approach: | They construct a methodological inspiration retrieval task using a citation-based methodology adjacency graph and embed an "intuitive prior'' into dense retrievers. |
| Outcome: | The proposed method achieves significant gains in Recall@3 and mAP over strong baselines. |
Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation (2026.findings-acl)
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| Challenge: | Language models are accelerating scientific research by automating hypothesis generation and implementation. |
| Approach: | They ask whether LMs can forecast the empirical success of research ideas before experiments . they frame evaluation as a reasoning task via Reinforcement Learning with Verifiable Rewards . |
| Outcome: | The proposed model outperforms off-the-shelf models in 77.1% of the evaluations . the model outpersforms GPT-5 in the evaluation of 11,488 idea pairs . |
IRIS: Interactive Research Ideation System for Accelerating Scientific Discovery (2025.acl-demo)
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| Challenge: | Recent work on automated hypothesis generation focuses on multi-agent frameworks and extending test-time compute, but none incorporates human-in-the-loop (HITL) integration. |
| Approach: | They propose an open-source platform to enable researchers to leverage LLM-assisted scientific ideation. |
| Outcome: | The proposed system empowers researchers with greater control throughout ideation process. |