6 papers
When Harness Beats Scale, and When Reading Beats Both
Ivan Bondarenko, Nikolay O. Nikitin
We describe our system for DocSem, the document-grounded quantitative reasoning shared task at DocInsights 2026, and analyze why it succeeded on labeled data and failed on the test…
RAGU: A Multi-Step GraphRAG Engine with a Compact Domain-Adapted LLM
Mikhail Komarov, Ivan Bondarenko, Stanislav Shtuka +5
Graph retrieval-augmented generation (GraphRAG) enhances large language models with structured knowledge, yet existing systems construct knowledge graphs in a single extraction pas…
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…
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…
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…
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…