SmartBench: Is Your LLM Truly a Good Chinese Smartphone Assistant? (2025.emnlp-main)
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| Challenge: | Existing evaluation benchmarks for Large Language Models focus on objective tasks like mathematics and coding in English, which do not reflect the practical use cases of on-device LLMs in real-world mobile scenarios. |
| Approach: | They propose a benchmark to evaluate the capabilities of on-device Large Language Models in Chinese mobile contexts. |
| Outcome: | The proposed framework evaluates on-device LLMs and MLLMs in Chinese . it provides a standardized framework for evaluating LLM performance on real smartphones . |
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| Challenge: | Existing state-of-the-art LLMs cannot perform well in situations where instructions are invalid or multiple devices are involved. |
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TRUEBench: Can LLM Response Meet Real-world Constraints as Productivity Assistant? (2025.findings-emnlp)
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AlignBench: Benchmarking Chinese Alignment of Large Language Models (2024.acl-long)
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Mobile-Bench: An Evaluation Benchmark for LLM-based Mobile Agents (2024.acl-long)
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MobileBench-OL: A Comprehensive Chinese Benchmark for Evaluating Mobile GUI Agents in Real-World Environment (2026.findings-acl)
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| Challenge: | Recent advances in mobile Graphical User Interface (GUI) agents highlight the growing need for comprehensive evaluation benchmarks. |
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