1 citations · 1 across the 12 of their papers we have counts for
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BiCA: Effective Biomedical Dense Retrieval with Citation-Aware Hard Negatives
Aarush Sinha, Pavan Kumar S, Roshan Balaji +1
Hard negatives are essential for training effective retrieval models. Hard-negative mining typically relies on ranking documents using cross-encoders or static embedding models bas…
Don't Retrieve, Generate: Prompting LLMs for Synthetic Training Data in Dense Retrieval
Aarush Sinha
Training effective dense retrieval models typically relies on hard negative (HN) examples mined from large document corpora using methods such as BM25 or cross-encoders, which requ…
GMLM: Bridging Graph Neural Networks and Language Models for Heterophilic Node Classification
Aarush Sinha
Integrating Pre-trained Language Models (PLMs) with Graph Neural Networks (GNNs) remains a central challenge in text-rich heterophilic graph learning. We propose a novel integratio…
Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation
Jaskaran Singh Walia, Aarush Sinha, Naman Saraswat +2
Financial bond yield forecasting is challenging due to data scarcity, nonlinear macroeconomic dependencies, and evolving market conditions. In this paper, we propose a novel framew…
ArxEval: Evaluating Retrieval and Generation in Language Models for Scientific Literature
Aarush Sinha, Viraj Virk, Dipshikha Chakraborty +1
Language Models [LMs] are now playing an increasingly large role in information generation and synthesis; the representation of scientific knowledge in these systems needs to be hi…