Evaluating LLM Reasoning in the Operations Research Domain with ORQA Article Swipe
Mahdi Mostajabdaveh
,
Timothy T. Yu
,
S. Dash
,
Rindranirina Ramamonjison
,
Jabo Serge Byusa
,
Giuseppe Carenini
,
Zirui Zhou
,
Yong Zhang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2412.17874
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2412.17874
In this paper, we introduce and apply Operations Research Question Answering (ORQA), a new benchmark designed to assess the generalization capabilities of Large Language Models (LLMs) in the specialized technical domain of Operations Research (OR). This benchmark evaluates whether LLMs can emulate the knowledge and reasoning skills of OR experts when confronted with diverse and complex optimization problems. The dataset, developed by OR experts, features real-world optimization problems that demand multistep reasoning to construct their mathematical models. Our evaluations of various open source LLMs, such as LLaMA 3.1, DeepSeek, and Mixtral, reveal their modest performance, highlighting a gap in their ability to generalize to specialized technical domains. This work contributes to the ongoing discourse on LLMs generalization capabilities, offering valuable insights for future research in this area. The dataset and evaluation code are publicly available.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2412.17874
- https://arxiv.org/pdf/2412.17874
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405783457
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4405783457Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2412.17874Digital Object Identifier
- Title
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Evaluating LLM Reasoning in the Operations Research Domain with ORQAWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-12-22Full publication date if available
- Authors
-
Mahdi Mostajabdaveh, Timothy T. Yu, S. Dash, Rindranirina Ramamonjison, Jabo Serge Byusa, Giuseppe Carenini, Zirui Zhou, Yong ZhangList of authors in order
- Landing page
-
https://arxiv.org/abs/2412.17874Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2412.17874Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2412.17874Direct OA link when available
- Concepts
-
Domain (mathematical analysis), Computer science, Management science, Engineering, Mathematics, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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