---
title: "China Mobile — works of 2026: 9 papers, the most cited first"
description: "9 works of China Mobile from 2026 in our library, the most cited first. Among them: SAFE-QAQ: End-to-End Slow-Thinking Audio-Text Fraud…"
canonical: "https://research.elamur.ai/free/en/companies/china-mobile/year/2026/"
---
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# Works of China Mobile from 2026

9 works · the most cited first · [← China Mobile](https://md.research.elamur.ai/free/en/companies/china-mobile/)

1. **[SAFE-QAQ: End-to-End Slow-Thinking Audio-Text Fraud Detection via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-safe-qaq-end-end-slow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peidong Wang, Zhiming Ma, Xin Dai, et al.*2026 · 3 citations*
2. **[AlphaQT-Bench: Diagnosing the Gap between Financial Code Generation and Quantitative Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/luo-2026-alphaqt-bench-diagnosing-gap-between/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sichun Luo, Yi Huang, Shichang Meng, et al.*2026*
3. **[ChildEval:WHEN LARGE LANGUAGE MODELS MEET CHILDREN'S PERSONALITIES](https://md.research.elamur.ai/free/en/papers/luo-2026-childeval-when-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanyan Luo, Xue Han, Chunxu Zhao, et al.*2026*
4. **[HeteroCache: A Dynamic Retrieval Approach to Heterogeneous KV Cache Compression for Long-Context LLM Inference](https://md.research.elamur.ai/free/en/papers/shi-2026-heterocache-dynamic-retrieval-approach-heterogeneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyuan Shi, Qibo Qiu, Xuefeng, et al.*2026*
5. **[ModularMoE: Fast LLM Customization with Parameter-Sharing Mixture-of-Experts for Low-Resource Settings](https://md.research.elamur.ai/free/en/papers/liu-2026-modularmoe-fast-llm-customization-parameter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaxing Liu, Qi Qi, Haifeng Sun, et al.*2026*
6. **[PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/shen-2026-pegrl-improving-machine-translation-post/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yunzhi Shen, Hao Zhou, Xin Huang, et al.*2026*
7. **[Soft Orthogonal Low-Rank Adaptation for Knowledge Sharing in Large Language Model Continual Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-soft-orthogonal-low-rank-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yitong Wang, Xue Han, WenChun Gao, et al.*2026*
8. **[Targeting the Needle, Ignoring the Haystack: Anchoring Crucial Cues for Evolving Scam Call Detection via an LLM-Assisted Classifier](https://md.research.elamur.ai/free/en/papers/wu-2026-targeting-needle-ignoring-haystack-anchoring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tong Wu, Qinliang Su, Jianxing Yu, et al.*2026*
9. **[iTAG: Inverse Design for Natural Text Generation with Accurate Causal Graph Annotations](https://md.research.elamur.ai/free/en/papers/wang-2026-itag-inverse-design-natural-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenshuo Wang, Boyu Cao, Nan Zhuang, et al.*2026*
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