2 citations · 2 across the 4 of their papers we have counts for
8 papers
Cyclic Counterfactuals under Shift-Scale Interventions
Saptarshi Saha, Dhruv Vansraj Rathore, Utpal Garain
Most counterfactual inference frameworks traditionally assume acyclic structural causal models (SCMs), i.e. directed acyclic graphs (DAGs). However, many real-world systems (e.g. b…
On Measuring Intrinsic Causal Attributions in Deep Neural Networks
Saptarshi Saha, Dhruv Vansraj Rathore, Soumadeep Saha +2
Quantifying the causal influence of input features within neural networks has become a topic of increasing interest. Existing approaches typically assess direct, indirect, and tota…
sudoLLM: On Multi-role Alignment of Language Models
Soumadeep Saha, Akshay Chaturvedi, Joy Mahapatra +1
User authorization-based access privileges are a key feature in many safety-critical systems, but have not been extensively studied in the large language model (LLM) realm. In this…
Square Kilometre Array Science Data Challenge 3a: foreground removal for an EoR experiment
A. Bonaldi, P. Hartley, R. Braun +179
We present and analyse the results of the Science data challenge 3a (SDC3a, https://sdc3.skao.int/challenges/foregrounds), an EoR foreground-removal community-wide exercise organis…
Factual Inconsistency in Data-to-Text Generation Scales Exponentially with LLM Size: A Statistical Validation
Joy Mahapatra, Soumyajit Roy, Utpal Garain
Monitoring factual inconsistency is essential for ensuring trustworthiness in data-to-text generation (D2T). While large language models (LLMs) have demonstrated exceptional perfor…
Deep Learning Based Recalibration of SDSS and DESI BAO Alleviates Hubble and Clustering Tensions
Rahul Shah, Purba Mukherjee, Soumadeep Saha +2
Conventional calibration of Baryon Acoustic Oscillations (BAO) data relies on estimation of the sound horizon at drag epoch from early universe observations by assuming a cos…