Vinay Kumar Sankarapu

According to our database, Vinay Kumar Sankarapu authored at least 22 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Shaping the Prior: How Synthetic Task Distributions Determine Tabular Foundation Model Quality.

Mohamed Bouadi, Nassim Bouarour, Varun Kulkarni, Shivam Dubey, Aditya Tanna, Vinay Kumar Sankarapu

CoRR, May, 2026

Distilling Tabular Foundation Models for Structured Health Data.

Aditya Tanna, Nassim Bouarour, Mohamed Bouadi, Vinay Kumar Sankarapu, Pratinav Seth

CoRR, May, 2026

Ensembling Tabular Foundation Models - A Diversity Ceiling And A Calibration Trap.

Aditya Tanna, Yash Desai, Pratinav Seth, Mohamed Bouadi, Nassim Bouarour, Vinay Kumar Sankarapu

CoRR, May, 2026

Pocket Foundation Models: Distilling TFMs into CPU-Ready Gradient-Boosted Trees.

Aditya Tanna, Nassim Bouarour, Mohamed Bouadi, Vinay Kumar Sankarapu, Pratinav Seth

CoRR, May, 2026

Data Presentation Over Architecture: Resampling Strategies for Credit Risk Prediction with Tabular Foundation Models.

Aditya Tanna, Mitul Solanki, Mohamed Bouadi, Nassim Bouarour, Pratinav Seth, Vinay Kumar Sankarapu

CoRR, May, 2026

Position: Behavioural Assurance Cannot Verify the Safety Claims Governance Now Demands.

Pratinav Seth, Vinay Kumar Sankarapu

CoRR, May, 2026

Forgetting That Sticks: Quantization-Permanent Unlearning via Circuit Attribution.

Saisab Sadhu, Pratinav Seth, Vinay Kumar Sankarapu

CoRR, May, 2026

AlignTune: Modular Toolkit for Post-Training Alignment of Large Language Models.

R. E. Zera Marveen Lyngkhoi, Chirag Chawla, Pratinav Seth, Utsav Avaiya, Soham Bhattacharjee, Mykola Khandoga, Rui Yuan, Vinay Kumar Sankarapu

CoRR, February, 2026

Beyond Uniform Credit: Causal Credit Assignment for Policy Optimization.

Mykola Khandoga, Rui Yuan, Vinay Kumar Sankarapu

CoRR, February, 2026

C-ΔΘ: Circuit-Restricted Weight Arithmetic for Selective Refusal.

Aditya Kasliwal, Pratinav Seth, Vinay Kumar Sankarapu

CoRR, February, 2026

Beyond KL Divergence: Policy Optimization with Flexible Bregman Divergences for LLM Reasoning.

Rui Yuan, Mykola Khandoga, Vinay Kumar Sankarapu

CoRR, February, 2026

TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models.

Aditya Tanna, Pratinav Seth, Mohamed Bouadi, Vinay Kumar Sankarapu

Proceedings of the Companion Proceedings of the ACM Web Conference 2026, 2026

Exploring Fine-Tuning for Tabular Foundation Models.

Aditya Tanna, Pratinav Seth, Mohamed Bouadi, Vinay Kumar Sankarapu

Proceedings of the ACM Web Conference 2026, 2026

Orion-Bix: Bi-Axial Attention for Tabular In-Context Learning.

Mohamed Bouadi, Pratinav Seth, Aditya Tanna, Vinay Kumar Sankarapu

Proceedings of the ACM Web Conference 2026, 2026

2025

Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning.

Mohamed Bouadi, Pratinav Seth, Aditya Tanna, Vinay Kumar Sankarapu

CoRR, November, 2025

TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models.

Aditya Tanna, Pratinav Seth, Mohamed Bouadi, Utsav Avaiya, Vinay Kumar Sankarapu

CoRR, November, 2025

Interpretability as Alignment: Making Internal Understanding a Design Principle.

Aadit Sengupta, Pratinav Seth, Vinay Kumar Sankarapu

CoRR, September, 2025

Bridging the Gap in XAI-Why Reliable Metrics Matter for Explainability and Compliance.

Pratinav Seth, Vinay Kumar Sankarapu

CoRR, February, 2025

xai_evals : A Framework for Evaluating Post-Hoc Local Explanation Methods.

Pratinav Seth, Yashwardhan Rathore, Neeraj Kumar Singh, Chintan Chitroda, Vinay Kumar Sankarapu

CoRR, February, 2025

Interpretability-Aware Pruning for Efficient Medical Image Analysis.

Nikita Malik, Pratinav Seth, Neeraj Kumar Singh, Chintan Chitroda, Vinay Kumar Sankarapu

Proceedings of the Efficient Medical Artificial Intelligence, 2025

DLBacktrace: Model Agnostic Explainability for any Deep Learning Model.

Vinay Kumar Sankarapu, Chintan Chitroda, Yashwardhan Rathore, Neeraj Kumar Singh, Pratinav Seth

Proceedings of the International Joint Conference on Neural Networks, 2025

2024

DLBacktrace: A Model Agnostic Explainability for any Deep Learning Models.

Vinay Kumar Sankarapu, Chintan Chitroda, Yashwardhan Rathore, Neeraj Kumar Singh, Pratinav Seth

CoRR, 2024