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Who cites «HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly»

54 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · ← back to «HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly»

  1. Phi-4 Technical ReportarXiv:2412.08905Marah Abdin, Jyoti Aneja, Harkirat Behl, et al.2024 · 502 citations
  2. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
  3. LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context MultitasksarXiv:2412.15204Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.2024 · 135 citations
  4. GLM-5: from Vibe Coding to Agentic EngineeringarXiv:2602.15763Aohan Zeng, Xin Lv, Zhenyu Hou, et al.2026 · 95 citations
  5. Kimi Linear: An Expressive, Efficient Attention ArchitecturearXiv:2510.26692Kimi Team, Yu Zhang, Zongyu Lin, et al.2025 · 51 citations
  6. Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and PerformancearXiv:2507.22448Jingwei Zuo, Maksim Velikanov, Ilyas Chahed, et al.2025 · 15 citations

41 more papers of our library cite it; they have no page here yet.

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