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cs.CL2026
Hierarchical Embedding Fusion for Retrieval-Augmented Code Generation
Nikita Sorokin, Ivan Sedykh, Valentin Malykh
Retrieval-augmented code generation often conditions the decoder on large retrieved code snippets. This ties online inference cost to repository size and introduces noise from long…
cs.CL2025
Iterative Self-Training for Code Generation via Reinforced Re-Ranking
Nikita Sorokin, Ivan Sedykh, Valentin Malykh
Generating high-quality code that solves complex programming tasks is challenging, especially with current decoder-based models that produce highly stochastic outputs. In code gene…
cs.CL2024
Searching by Code: a New SearchBySnippet Dataset and SnippeR Retrieval Model for Searching by Code Snippets
Ivan Sedykh, Dmitry Abulkhanov, Nikita Sorokin +2
Code search is an important and well-studied task, but it usually means searching for code by a text query. We argue that using a code snippet (and possibly an error traceback) as…