Self-Guided Test-Time Training gives +15% long-context accuracy by picking its own evidence spans.

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.