21 citations · 30 across the 11 of their papers we have counts for
11 papers
CircuitKIT : Circuit Discovery, Evaluation, and Application Toolkit for Mechanistic Interpretability
Pratinav Seth, Hem Gosalia, Aditya Kasliwal +1
Circuit analysis can support not only model explanation but also downstream interventions such as pruning, editing, steering, and selective fine-tuning. However, conducting such an…
LEMMA: Laplacian pyramids for Efficient Marine SeMAntic Segmentation
Ishaan Gakhar, Laven Srivastava, Sankarshanaa Sagaram +2
Semantic segmentation in marine environments is crucial for the autonomous navigation of unmanned surface vessels (USVs) and coastal Earth Observation events such as oil spills. Ho…
-: Circuit-Restricted Weight Arithmetic for Selective Refusal
Aditya Kasliwal, Pratinav Seth, Vinay Kumar Sankarapu
Modern deployments require LLMs to enforce safety policies at scale, yet many controls rely on inference-time interventions that add recurring compute cost and serving complexity.…
Localizing and Mitigating Memorization in Image Autoregressive Models
Aditya Kasliwal, Franziska Boenisch, Adam Dziedzic
Image AutoRegressive (IAR) models have achieved state-of-the-art performance in speed and quality of generated images. However, they also raise concerns about memorization of their…
HipyrNet: Hypernet-Guided Feature Pyramid network for mixed-exposure correction
Shaurya Singh Rathore, Aravind Shenoy, Krish Didwania +2
Recent advancements in image translation for enhancing mixed-exposure images have demonstrated the transformative potential of deep learning algorithms. However, addressing extreme…
LapGSR: Laplacian Reconstructive Network for Guided Thermal Super-Resolution
Aditya Kasliwal, Ishaan Gakhar, Aryan Kamani +2
In the last few years, the fusion of multi-modal data has been widely studied for various applications such as robotics, gesture recognition, and autonomous navigation. Indeed, hig…
AgriLLM: Harnessing Transformers for Farmer Queries
Krish Didwania, Pratinav Seth, Aditya Kasliwal +1
Agriculture, vital for global sustenance, necessitates innovative solutions due to a lack of organized domain experts, particularly in developing countries where many farmers are i…
Solar Panel Segmentation :Self-Supervised Learning Solutions for Imperfect Datasets
Sankarshanaa Sagaram, Krish Didwania, Laven Srivastava +3
The increasing adoption of solar energy necessitates advanced methodologies for monitoring and maintenance to ensure optimal performance of solar panel installations. A critical co…
ReFuSeg: Regularized Multi-Modal Fusion for Precise Brain Tumour Segmentation
Aditya Kasliwal, Sankarshanaa Sagaram, Laven Srivastava +2
Semantic segmentation of brain tumours is a fundamental task in medical image analysis that can help clinicians in diagnosing the patient and tracking the progression of any malign…
CoReFusion: Contrastive Regularized Fusion for Guided Thermal Super-Resolution
Aditya Kasliwal, Pratinav Seth, Sriya Rallabandi +1
Thermal imaging has numerous advantages over regular visible-range imaging since it performs well in low-light circumstances. Super-Resolution approaches can broaden their usefulne…
Performance evaluation of deep segmentation models for Contrails detection
Akshat Bhandari, Sriya Rallabandi, Sanchit Singhal +2
Contrails, short for condensation trails, are line-shaped ice clouds produced by aircraft engine exhaust when they fly through cold and humid air. They generate a greenhouse effect…