Mainak Singha

Orcid: 0000-0002-7615-2575

According to our database1, Mainak Singha authored at least 27 papers between 2023 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
BioVLM: Routing Prompts, Not Parameters, for Cross-Modality Generalization in Biomedical VLMs.
CoRR, April, 2026

GeoMeld: Toward Semantically Grounded Foundation Models for Remote Sensing.
CoRR, April, 2026

CLIPoint3D: Language-Grounded Few-Shot Unsupervised 3D Point Cloud Domain Adaptation.
CoRR, February, 2026

bi-modal textual prompt learning for vision-language models in remote sensing.
CoRR, January, 2026

MMLGNet: Cross-Modal Alignment of Remote Sensing Data using CLIP.
CoRR, January, 2026

SDHSI-Net: Learning Better Representations for Hyperspectral Images via Self-Distillation.
CoRR, January, 2026

Reconstruction Guided Few-shot Network For Remote Sensing Image Classification.
CoRR, January, 2026

2025
How (Mis)calibrated is Your Federated CLIP and What To Do About It?
CoRR, December, 2025

Detecting AI Hallucinations in Finance: An Information-Theoretic Method Cuts Hallucination Rate by 92%.
CoRR, December, 2025

Learning Under Laws: A Constraint-Projected Neural PDE Solver that Eliminates Hallucinations.
CoRR, November, 2025

FedMVP: Federated Multi-modal Visual Prompt Tuning for Vision-Language Models.
CoRR, April, 2025

Towards molecular structure discovery from cryo-ET density volumes via modelling auxiliary semantic prototypes.
Briefings Bioinform., January, 2025

Meta-Learning to Teach Semantic Prompts for Open Domain Generalization in Vision-Language Models.
Trans. Mach. Learn. Res., 2025

RS3Lip: Consistency for remote sensing image classification on part embeddings using self-supervised learning and CLIP.
Comput. Vis. Image Underst., 2025

FedMVP: Federated Multimodal Visual Prompt Tuning for Vision-Language Models.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

OSLoPrompt: Bridging Low-Supervision Challenges and Open-Set Domain Generalization in CLIP.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalization.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

GraphVL: Graph-Enhanced Semantic Modeling via Vision-Language Models for Generalized Class Discovery✱.
Proceedings of the Fifteenth Indian Conference on Computer Vision Graphics and Image Processing, 2024

Elevating All Zero-Shot Sketch-Based Image Retrieval Through Multimodal Prompt Learning.
Proceedings of the Computer Vision - ECCV 2024, 2024

Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

CDAD-Net: Bridging Domain Gaps in Generalized Category Discovery.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

COSMo: CLIP Talks on Open-Set Multi-Target Domain Adaptation.
Proceedings of the 35th British Machine Vision Conference, 2024

2023
HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023

C-SAW: Self-Supervised Prompt Learning for Image Generalization in Remote Sensing.
Proceedings of the Fourteenth Indian Conference on Computer Vision, 2023

AD-CLIP: Adapting Domains in Prompt Space Using CLIP.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIP.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

GOPro: Generate and Optimize Prompts in CLIP using Self-Supervised Learning.
Proceedings of the 34th British Machine Vision Conference 2023, 2023


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