@inproceedings{chernyshevich-2025-core,
title = "Core Intelligence at {S}em{E}val-2025 Task 8: Multi-hop {LLM} Agent for Tabular Question Answering",
author = "Chernyshevich, Maryna",
editor = "Rosenthal, Sara and
Ros{\'a}, Aiala and
Ghosh, Debanjan and
Zampieri, Marcos",
booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.semeval-1.174/",
pages = "1313--1317",
ISBN = "979-8-89176-273-2",
abstract = "This paper describes a multi-hop LLM agent for tabular question answering developed for SemEval-2025 Task 8 and ranked 6th with 87{\%} accuracy. Our approach combines proprietary LLM (ChatGPT-3.5-turbo) for code generation and open source LLM (Llama-3.2-3B) for answer validation."
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%0 Conference Proceedings
%T Core Intelligence at SemEval-2025 Task 8: Multi-hop LLM Agent for Tabular Question Answering
%A Chernyshevich, Maryna
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F chernyshevich-2025-core
%X This paper describes a multi-hop LLM agent for tabular question answering developed for SemEval-2025 Task 8 and ranked 6th with 87% accuracy. Our approach combines proprietary LLM (ChatGPT-3.5-turbo) for code generation and open source LLM (Llama-3.2-3B) for answer validation.
%U https://aclanthology.org/2025.semeval-1.174/
%P 1313-1317
Markdown (Informal)
[Core Intelligence at SemEval-2025 Task 8: Multi-hop LLM Agent for Tabular Question Answering](https://aclanthology.org/2025.semeval-1.174/) (Chernyshevich, SemEval 2025)
ACL