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Research2026-07-13 · source-backed
Test-time training for long-context LLMs is highly sensitive to which spans you train on. Random spans degrade accuracy because most are irrelevant (arXiv:2607.09415). S-TTT has the model first identify relevant evidence passages, then run adaptation only on those, for up to 15% relative gains on LongBench-v2 and LongBench-Pro with Qwen3-4B-Thinking and Llama-3.1-8B. The builder takeaway: TTT is practical for long documents if you gate what the model learns from at inference time. Don't adapt on the whole haystack.
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Meta released Llama / Shared entity: Qwen3 / Same source domain / What happened next / Tension
Linked by a graph relationship (Meta released Llama); both cover Qwen3; reported by the same outlet (arxiv.org).
Meta released Llama / Shared entities / What happened next
Linked by a graph relationship (Meta released Llama); both cover Qwen3, Test; picks up the Qwen3 thread on 2026-08-10.
Meta released Llama / Shared entities / Earlier coverage
Linked by a graph relationship (Meta released Llama); both cover Llama, Test; earlier Llama coverage from 2026-05-01.
Linked by a graph relationship (Meta released Llama); both cover Llama, Qwen3; earlier Llama coverage from 2026-04-02.
Meta released Llama / Shared entity: Qwen3 / Same source domain / What happened next
Linked by a graph relationship (Meta released Llama); both cover Qwen3; reported by the same outlet (arxiv.org).
Meta released Llama / Shared entity: Qwen3 / What happened next
Linked by a graph relationship (Meta released Llama); both cover Qwen3; picks up the Qwen3 thread on 2026-08-20.
Meta released Llama / Shared entity: Llama / What happened next
Linked by a graph relationship (Meta released Llama); both cover Llama; picks up the Llama thread on 2026-08-16.
Meta released Llama / Shared entity: LLMs / What happened next
Linked by a graph relationship (Meta released Llama); both cover LLMs; picks up the LLMs thread on 2026-07-27.