Mingyang Song
Mingyang Song has 4 papers in our library, in 2025–2026, most of them on Language models & pretraining, Machine translation, Evaluation & benchmarks; often with Mao Zheng, Xuan Luo, Zheng Li.
OpenAlex · ORCID · Wikidata · h-index 83 · 957 works · 28,348 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 56 times in our library · ⭐ Paper Stars ranking: #7637
Affiliations
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksComputer Vision and Pattern Recognition · 1 workInformation Systems · 1 work
🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 3 worksMachine translation · 2 worksEvaluation & benchmarks · 1 work
Works by year
2020s
Papers
- Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language Models (2025 · 20 citations)
Popular long-context tests such as needle-in-a-haystack ask a model to find one inserted sentence. Recent LLMs score almost perfectly on them, so these tests no longer separate strong models from weak ones. The authors propose Counting-Stars, a benchmark that measures how well a model gathers many scattered pieces of… - Hunyuan-MT Technical Report (2025 · 17 citations)
Open-source LLM translators still trail proprietary systems, and translation between Mandarin and China's minority languages gets little attention. - SSR-Zero: Simple Self-Rewarding Reinforcement Learning for Machine Translation (2026 · 10 citations)
Most strong LLM-based machine translation (MT) systems depend on costly external supervision, such as human-made reference translations or trained reward models, and this limits how far they can scale. - Can Many-Shot In-Context Learning Help LLMs as Evaluators? A Preliminary Empirical Study (2025 · 9 citations)
LLM judges are increasingly used to grade other models, but their scores can be unstable and skewed by hidden biases.
Co-authors here
Venues
- International Conference on Computational Linguistics (COLING) ×2: COLING 2025 ×2
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
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