---
title: "Kun Wang — papers of 2026 — 9 papers, the most cited first"
description: "Kun Wang — papers of 2026: 9 papers on Elamur Research, the most cited first — what each work is about in our own words."
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# Kun Wang — papers of 2026 — 9 papers, the most cited first

9 papers · [all years of Kun Wang](https://md.research.elamur.ai/free/en/authors/kun-wang/#years)

**[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*

**[CORBA: Contagious Recursive Blocking Attacks on Multi-Agent Systems Based on Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-corba-contagious-recursive-blocking-attacks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenhong Zhou, Zherui Li, Jie Zhang, et al.*2026 · 7 citations*

**[Streaming Hallucination Detection in Long Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/lu-2026-streaming-hallucination-detection-long-chain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haolang Lu, Minghui Pan, Ripeng LI, et al.*2026 · 1 citation*

**[Calibrating Inference Time Alignment with Sequence-level Risk Accumulation](https://md.research.elamur.ai/free/en/papers/tan-2026-calibrating-inference-time-alignment-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shanwen Tan, Ziyang Dong, Wei Ju, et al.*2026*

**[CIA: Inferring the Communication Topology from LLM-based Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/wu-2026-cia-inferring-communication-topology-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongxuan Wu, Xixun Lin, He Zhang, et al.*2026*

**[GaLa: Hypergraph-Guided Visual Language Models for Procedural Planning](https://md.research.elamur.ai/free/en/papers/wang-2026-gala-hypergraph-guided-visual-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kun Wang, Li Yiming, Mingcheng Qu, et al.*2026*

**[HearSay Benchmark: Do Audio LLMs Leak What They Hear?](https://md.research.elamur.ai/free/en/papers/wang-2026-hearsay-benchmark-do-audio-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jin Wang, Kaiwen Luo, Liang Lin, et al.*2026*

**[RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios](https://md.research.elamur.ai/free/en/papers/zhang-2026-rsa-bench-benchmarking-audio-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Zhang, Kaiwen Luo, Liang Lin, et al.*2026*

**[Scaling Law for Multimodal Large Language Model Supervised Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-scaling-law-multimodal-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YiFan Zhang, Tao Yu, Feng Li, et al.*2026*