3 papers
cs.LG2026
Counterfactual Peptide Editing for Causal TCR--pMHC Binding Inference
Sanjar Khudoyberdiev, Arman Bekov
Neural models for TCR-pMHC binding prediction are susceptible to shortcut learning: they exploit spurious correlations in training data -- such as peptide length bias or V-gene co-…
cs.GR2026
Calibrated Abstention for Reliable TCR--pMHC Binding Prediction under Epitope Shift
Arman Bekov, Timur Bekzhanov, Bekzat Sadykov
Predicting T-cell receptor (TCR)--peptide-MHC (pMHC) binding is central to vaccine design and T-cell therapy, yet deployed models frequently encounter epitopes unseen during traini…
cs.GR2026
Predicting User Satisfaction in Online Education Platforms: A Large Language Model Based Multi-Modal Review Mining Framework
Arman Bekov, Azamat Nurgali
Online education platforms have experienced explosive growth over the past decade, generating massive volumes of user-generated content in the form of reviews, ratings, and behavio…