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Rasul Khanbayov

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#machine learning Preprint Oct 2026

The Gradient That Top-k Distillation Never Computes

Many deployed distillation pipelines show the student a truncated view of the teacher: keep the top-k probabilities, renormalize, and minimize a divergence on what remains. Renormalization is assumed to account for the missing mass. We prove that it removes the visibility of tail mass, not the freedom to move it. The r...

Rasul Khanbayov, Hasan Kurban · 0 citations
Preprint Sep 2026

PhysWeep: Does a Video Generator Realize the Physics You Ask For?

Image-to-video generators are often credited with absorbing physical dynamics as implicit world models, a claim the community currently checks with plausibility scores that ask whether a clip looks consistent with real-world motion. Plausibility is the wrong test on its own, because a clip can look natural while encodi...

Rasul Khanbayov, Hasan Kurban · 2 citations
Preprint Sep 2026

Physics as the label for measuring and correcting materials reasoning in multimodal models

Vision-language and language models increasingly interpret materials data, yet benchmarks report that they hallucinate invalid properties and violate physical law. Evaluation matches final answers to scarce human labels, while discovery agents verify final proposals or density functional theory (DFT) execution. Neither...

Hasan Kurban, Rasul Khanbayov, Mustafa Kurban · 0 citations
Preprint Aug 2026

Counterfactual Sensitivity Is Not Repairability: Auditing Replay Probes for Video Evidence

CARVE is introduced, a black-box counterfactual probe that compares answer changes under matched SHAM and DESTROY replays, and shows only a weak association with annotated temporal coverage, so CARVE is best understood as a routing signal rather than a direct grounding classifier.

Rama Y. AlHamidi, Rasul Khanbayov, E. Serpedin et al. · 0 citations
Preprint Aug 2026

Conformal Coverage Guarantees for Any Video Temporal Grounder

C COVER changes the output object: a post-hoc, model-agnostic wrapper that turns any grounder, a trained localizer or a black-box video--language model, into one that emits a temporal region containing the true moment with probability at least $1-\alpha$, by calibrating the quantile of a temporal nonconformity score on...

Aseel A. Mohamed, Rasul Khanbayov, E. Serpedin et al. · 0 citations

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