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Aritra Das

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Preprint Aug 2026

The Query Knows What to Forget: A Second Erase Direction for Linear Attention

Linear attention keeps a state of fixed size. At long context, many stored items share this state, and interference between them degrades retrieval. Gated DeltaNet-2 (GDN-2), like every delta-rule model before it, derives its erase vector from the key of the current token. However, the interference in its reads is meas...

Dhruman Gupta, Aritra Das, Debayan Gupta · 0 citations
#artificial intelligence Preprint Aug 2026

Identifying Intelligent Processes via Online Sequential Testing

This work formalizes the two levels of active sequential hypothesis testing as an outer probe-design problem and an inner identification problem, and shows that selecting which evaluations to construct at minimum cost, so that every pair of candidates is distinguished, is exactly a weighted set cover problem.

Aritra Das, Debayan Gupta · 0 citations
#machine learning Preprint Sep 2026

Symmetries and Singularities

This work studies the LLC of a graph attention model by exploiting symmetries in both the graph structure and the attention parameters, and develops an analytic framework through a teacher--student setting and explicit LLC estimates after considering the symmetry--induced degeneracies.

Vishnu Varadarajan, Mihir More, Aritra Das et al. · 0 citations

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