{"schema_version":"onlylabs.public_signal.v1","title":"Tencent Hunyuan Repo: Tencent-Hunyuan/HiLS-Attention","description":"Tencent Hunyuan repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/fb444f93-3fa4-420f-b520-be9dd79ad734","json_url":"https://onlylabs.fyi/signals/fb444f93-3fa4-420f-b520-be9dd79ad734/signal.json","generated_at":"2026-07-26T18:47:00.239Z","evidence_latest_fetched_at":"2026-07-08T07:01:28.940918+00:00","signal_first_seen_at":"2026-07-08T07:00:50.179871+00:00","org":{"slug":"tencent-hunyuan","name":"Tencent Hunyuan","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/tencent-hunyuan","dossier_json_url":"https://onlylabs.fyi/labs/tencent-hunyuan/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/fb444f93-3fa4-420f-b520-be9dd79ad734","signal_json":"https://onlylabs.fyi/signals/fb444f93-3fa4-420f-b520-be9dd79ad734/signal.json","source":"https://github.com/Tencent-Hunyuan/HiLS-Attention","lab_dossier":"https://onlylabs.fyi/labs/tencent-hunyuan","lab_dossier_json":"https://onlylabs.fyi/labs/tencent-hunyuan/dossier.json","analysis":"https://onlylabs.fyi/analysis/tencent-hunyuan","analysis_json":"https://onlylabs.fyi/analysis/tencent-hunyuan/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/tencent-hunyuan/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":null},"answer_pack":{"answer":"Tencent Hunyuan published Tencent-Hunyuan/HiLS-Attention (Python). 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HiLS-Attention is a chunk-wise sparse attention mechanism that learns chunk selection end-to-end under the language-modeling loss, enabling native sparse training for efficient long-context modeling. ![HiLS-Attention Overview](./assets/hils_attn_overview.png) *Figure: Overview of HiLS-Attention. Naive block sparse attention selects top-k chunks by their exact chunk mass, but computing all chunk masses requires full QK computation. 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