# EXAONE 3.0 7.8B Instruction Tuned Language Model

arXiv: https://arxiv.org/abs/2408.03541 · HTML: https://mlsanity.com/paper/2408.03541/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 29 references that are in the map.
- First posted on arXiv 7 Aug 2024.

## Builds on (most cited first, 19 of 19)

- [Training Verifiers to Solve Math Word Problems](https://mlsanity.com/paper/2110.14168/) (2021)
- [Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://mlsanity.com/paper/2306.05685/) (2023)
- [Evaluating Large Language Models Trained on Code](https://mlsanity.com/paper/2107.03374/) (2021)
- [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://mlsanity.com/paper/2305.18290/) (2023)
- [Measuring Massive Multitask Language Understanding](https://mlsanity.com/paper/2009.03300/) (2020)
- [Measuring Mathematical Problem Solving With the MATH Dataset](https://mlsanity.com/paper/2103.03874/) (2021)
- [Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge](https://mlsanity.com/paper/1803.05457/) (2018)
- [Program Synthesis with Large Language Models](https://mlsanity.com/paper/2108.07732/) (2021)
- [Gemma 2: Improving Open Language Models at a Practical Size](https://mlsanity.com/paper/2408.00118/) (2024)
- [GLU Variants Improve Transformer](https://mlsanity.com/paper/2002.05202/) (2020)
- [GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints](https://mlsanity.com/paper/2305.13245/) (2023)
- [Instruction-Following Evaluation for Large Language Models](https://mlsanity.com/paper/2311.07911/) (2023)
- [Ethical and social risks of harm from Language Models](https://mlsanity.com/paper/2112.04359/) (2021)
- [Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators](https://mlsanity.com/paper/2404.04475/) (2024)
- [DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining](https://mlsanity.com/paper/2305.10429/) (2023)
- [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://mlsanity.com/paper/2308.16884/) (2023)
- [WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild](https://mlsanity.com/paper/2406.04770/) (2024)
- [Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models](https://mlsanity.com/paper/2102.02503/) (2021)
- [Neural Machine Translation with Byte-Level Subwords](https://mlsanity.com/paper/1909.03341/) (2019)

## Built on by (most cited first, 21 of 21)

- [EXAONE 3.5: Series of Large Language Models for Real-world Use Cases](https://mlsanity.com/paper/2412.04862/) (2024)
- [LLM-as-a-Judge & Reward Model: What They Can and Cannot Do](https://mlsanity.com/paper/2409.11239/) (2024)
- [EXAONE 4.0: Unified Large Language Models Integrating Non-reasoning and Reasoning Modes](https://mlsanity.com/paper/2507.11407/) (2025)
- [Multiple LLM Agents Debate for Equitable Cultural Alignment](https://mlsanity.com/paper/2505.24671/) (2025)
- [InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU](https://mlsanity.com/paper/2502.08910/) (2025)
- [VARCO-VISION: Expanding Frontiers in Korean Vision-Language Models](https://mlsanity.com/paper/2411.19103/) (2024)
- [Nunchi-Bench: Benchmarking Language Models on Cultural Reasoning with a Focus on Korean Superstition](https://mlsanity.com/paper/2507.04014/) (2025)
- [LRAGE: Legal Retrieval Augmented Generation Evaluation Tool](https://mlsanity.com/paper/2504.01840/) (2025)
- [Mi:dm 2.0 Korea-centric Bilingual Language Models](https://mlsanity.com/paper/2601.09066/) (2026)
- [Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models](https://mlsanity.com/paper/2410.08731/) (2024)
- [Trillion 7B Technical Report](https://mlsanity.com/paper/2504.15431/) (2025)
- [Taxation Perspectives from Large Language Models: A Case Study on Additional Tax Penalties](https://mlsanity.com/paper/2503.03444/) (2025)
- [Evaluating Multimodal Generative AI with Korean Educational Standards](https://mlsanity.com/paper/2502.15422/) (2025)
- [Accurate Sublayer Pruning for Large Language Models by Exploiting Latency and Tunability Information](https://mlsanity.com/paper/2506.03510/) (2025)
- [Expanding Foundational Language Capabilities in Open-Source LLMs through a Korean Case Study](https://mlsanity.com/paper/2509.03972/) (2025)
- [Assessing Socio-Cultural Alignment and Technical Safety of Sovereign LLMs](https://mlsanity.com/paper/2510.14565/) (2025)
- [Korean Culture into LLM Alignment: Toward Cultural Coherence](https://mlsanity.com/paper/2606.06797/) (2026)
- [Theme-Explanation Structure for Table Summarization using Large Language Models: A Case Study on Korean Tabular Data](https://mlsanity.com/paper/2501.10487/) (2025)
- [SHREC 2025: Retrieval of Optimal Objects for Multi-modal Enhanced Language and Spatial Assistance (ROOMELSA)](https://mlsanity.com/paper/2508.08781/) (2025)
- [Ko-WideSearch: A Korean Breadth-Search Benchmark for Exhaustive Set Enumeration by Web Agents](https://mlsanity.com/paper/2606.27595/) (2026)
- [KoAGE: Do Large Language Models Know, Learn, and Coin Korean Neologisms?](https://mlsanity.com/paper/2610.19399/) (2026)

## Abstract (arXiv)

We introduce EXAONE 3.0 instruction-tuned language model, the first open model in the family of Large Language Models (LLMs) developed by LG AI Research. Among different model sizes, we publicly release the 7.8B instruction-tuned model to promote open research and innovations. Through extensive evaluations across a wide range of public and in-house benchmarks, EXAONE 3.0 demonstrates highly competitive real-world performance with instruction-following capability against other state-of-the-art open models of similar size. Our comparative analysis shows that EXAONE 3.0 excels particularly in Korean, while achieving compelling performance across general tasks and complex reasoning. With its strong real-world effectiveness and bilingual proficiency, we hope that EXAONE keeps contributing to advancements in Expert AI. Our EXAONE 3.0 instruction-tuned model is available at https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct.