The Election Commission of India (ECI) has extended the deadline for citizens to complete the Special Intensive Revision (SIR) enumeration process from December 4 to December 11, offering additional ...

With the ongoing Special Intensive Revision (SIR) of electoral rolls, voters who have submitted their enumeration forms can now verify online whether their Booth Level Officer (BLO) has uploaded their ...

If you recently submitted your Enumeration Form for SIR to your Booth Level Officer or through the online portal, you can easily verify whether your details have been digitised by the Election ...

Voters can submit claims and objections from December 19, 2025, to January 18, 2026. SIR enumeration form, which is a part of the larger Special Intensive Revision (SIR) of the electoral rolls being ...

The Election Commission of India (ECI) has initiated the Special Intensive Revision (SIR) process across multiple states, with booth-level officers distributing enumeration forms to electors. The SIR ...

The Special Intensive Revision (SIR) process is a major activity of the Election Commission of India to keep electoral rolls accurate, up to date, and free of errors, in advance of major elections. As ...

The process for the Special Intensive Revision (SIR) of electoral rolls have already started in West Bengal and people are submitting their SIR forms or Enumeration Form. If you have submitted the ...

If you have submitted your Enumeration Form, you can quickly check online whether your Booth Level Officer has digitised your details before the 4 December deadline. Voters who have submitted their ...

President Trump announced on Sunday that most Americans will receive “at least” $2,000 from the tariff revenue collected by the Trump administration. Trump’s statement, made early Sunday on his Truth ...

SIR in Bengal: In a major update for voters away from home or outside West Bengal, the Systematic Initiative for Revision (SIR) form is available online from Friday evening on the Election Commission ...

Abstract: Deep learning models are notoriously fragile when confronted with adversarial examples. In the realm of natural language processing (NLP), adversarial attacks are categorized into white box ...