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From the 1 of 6 linked papers with an AI index.

collaborators

6 papers

cs.CL2026

RAGU: A Multi-Step GraphRAG Engine with a Compact Domain-Adapted LLM

Mikhail Komarov, Ivan Bondarenko, Stanislav Shtuka +5

RAGU is an open‑source GraphRAG engine that separates entity extraction from consolidation using a two‑stage typed extraction, deduplication, summarization, and community detection…

cs.CL2026

RaguTeam at SemEval-2026 Task 8: Meno and Friends in a Judge-Orchestrated LLM Ensemble for Faithful Multi-Turn Response Generation

Ivan Bondarenko, Roman Derunets, Oleg Sedukhin +3

We present our winning system for Task~B (generation with reference passages) in SemEval-2026 Task~8: MTRAGEval. Our method is a heterogeneous ensemble of seven LLMs with two promp…

cs.CL2026

asr_eval: Algorithms and tools for multi-reference and streaming speech recognition evaluation

Oleg Sedukhin, Andrey Kostin

We propose several improvements to the speech recognition evaluation. First, we propose a string alignment algorithm that supports both multi-reference labeling, arbitrary-length i…

cs.CL2026

Pisets: A Robust Speech Recognition System for Lectures and Interviews

Ivan Bondarenko, Daniil Grebenkin, Oleg Sedukhin +3

This work presents a speech-to-text system "Pisets" for scientists and journalists which is based on a three-component architecture aimed at improving speech recognition accuracy w…

cs.SE2026

TAM-Eval: Evaluating LLMs for Automated Unit Test Maintenance

Elena Bruches, Vadim Alperovich, Dari Baturova +8

While Large Language Models (LLMs) have shown promise in software engineering, their application to unit testing remains largely confined to isolated test generation or oracle pred…

cs.SE2026

RM -RF: Reward Model for Run-Free Unit Test Evaluation

Elena Bruches, Daniil Grebenkin, Mikhail Klementev +8

We present RM-RF, a lightweight reward model for run-free evaluation of automatically generated unit tests. Instead of repeatedly compiling and executing candidate tests, RM-RF pre…