Author

Praveen Kumar Dhankar

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Conference Open access Sep 2026

Vision Language Models for Cross-Modal Retrieval

Contrastive Language–Image Pre-training (CLIP) gives strong zero-shot baselines for cross-modal retrieval, but full fine-tuning is costly and InfoNCE treats every non-matching pair as an equally wrong negative. We study parameter-efficient fine-tuning of CLIP ViT-B/32 on MS-COCO 2017 with three components added increme...

Pranjal Kumar Maurya, Sofia Singh, Rahul Agrawal et al. · 2026 10th International Conf... · 0 citations

Preprint Aug 2026

Testing $f(Q)$ Gravity with DESI DR2 and Strong-Lensing Time Delays

Symmetric teleparallel gravity provides an alternative description of gravitation in which non-metricity replaces curvature and torsion. Its extension through $f(Q)$ gravity offers a different geometric description of the late-time expansion of the Universe and its accelerated phase. In this work, we investigate two $f...

Darshan Kumar, Saibal Ray, Feng-Ge Zhang et al. · 0 citations

Conference Jul 2026

Parameter-Efficient Fine-Tuning of Transformer Models: An Empirical Study of LoRA Optimization for High-Cardinality Intent Classification

Although parameter-efficient fine-tuning significantly reduces the computing cost of deep models, default configurations are insufficient to perform as good as full fine-tuning for challenging large-cardinality intent detection problems with 77-151 intents. Thus, this work presents the S1 configuration that is proposed...

Harsh Anand, Sofia Singh, Rahul Agrawal et al. · 2026 International Conferenc... · 0 citations