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cs.CL2026
Prompt Embedding Probes (PEP): Hallucination Detection in LLMs from Hidden States
Zakhar Mrykhin, Valentin Malykh
Large language models (LLMs) can generate fluent and useful responses but remain prone to hallucinations. We introduce Prompt Embedding Probes (PEP), a white-box method for answer-…
cs.CL2024
CCT-Code: Cross-Consistency Training for Multilingual Clone Detection and Code Search
Anton Tikhonov, Nikita Sorokin, Dmitry Abulkhanov +3
We consider the well-known and important tasks of clone detection and information retrieval for source code. The most standard setup is to search clones inside the same language co…
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…