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Author

Shaswati Saha

4 papers indexed here

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#small language model Preprint Sep 2026

BEFORE THE FLIP: Measuring Hidden Score Shifts In Quantized Vision Language Models Before The Answer Changes for Visual Question Answering

Findings show that compression can alter the scores behind unchanged answers, but do not establish a reliable benefit from adjusting precision for each question, and whether choosing different groups for each question offers benefits beyond shuffled controls is tested.

Sourajit Saha, Shubhashis Roy Dipta, Shaswati Saha et al. · 1 citation
#artificial intelligence Preprint Sep 2026

New Evidence, Same Choice: Testing Physical Experiment Selection in Vision Language Models

Whether vision language models can decide when to answer immediately and, when more evidence is needed, which experiment to perform is studied to reveal limitations in physical reasoning that conventional answer accuracy can overlook.

Sourajit Saha, Shubhashis Roy Dipta, Nobin Sarwar et al. · 0 citations
#artificial intelligence Preprint Sep 2026

OracleZoom: On-Policy Self-Distillation Inspired Reference-Constrained Recursive Image Super Resolution

OracleZoom is presented, an on-policy distillation-inspired, reference-constrained framework that trains on its trajectory while carrying the last ground-truth evidence beyond the supervision boundary, and achieves the state-of-the-art SR quality across zooming scales.

Shubhashis Roy Dipta, Sourajit Saha, Shaswati Saha et al. · 1 citation
#computer vision Jul 2026

To Erase, or Not to Erase: Robust Training-Free Concept Erasure with Preservation aware Adaptive Ranked Subspace Expansion

Experiments on NSFW, artistic style, and object erasure, with a large-scale robustness-utility analysis over many CET baselines, show that PARSE erases multiple concepts robustly without sacrificing post-edit utility.

Shaswati Saha, Rajasekhar Anguluri, Manas Gaur · 3 citations

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