Tencent Hunyuan Proposes Hierarchical Sparse Attention for Long-Context Extrapolation
Tencent-Hunyuan · hf · 2026-07-08
The Tencent Hunyuan team proposed Hierarchical Landmark Sparse Attention, achieving efficient long-context language modeling through end-to-end block selection learning. This method performs on par with full attention while maintaining the ability to extrapolate beyond the training context length.
More from Research
- OpenAI says long-horizon models need safety and alignment checks across full action sequences — rhiever · 2026-07-22
- A Reddit user proposes a consistency LoRA to keep anime and game scenes visually stable — ThirdWorldBoy21 · 2026-07-22
- Graph workload 854.graph500 enters SPEC CPU 2026 as a new CPU benchmark — Prof_DavidBader · 2026-07-22
- BlackboxNLP 2026 is recruiting extra reviewers after a high submission volume — hanjie_chen · 2026-07-22
- AWS shows self-distilled reasoning can preserve math and coding skills during SFT — AWS ML Blog · 2026-07-22
- UI2App shows screenshot fidelity still lags real interaction recovery — Grace Man Chen · 2026-07-22