TRACE ranks CVE-to-ATT&CK mappings with constrained multi-evidence
Candidate construction cuts a 201-technique space by about 60% while retaining a ground-truth technique for 95.11%–100% of CVEs.
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Candidate construction cuts a 201-technique space by about 60% while retaining a ground-truth technique for 95.11%–100% of CVEs.
The attack needs no data-specific prior and was tested on TOFU, MUSE, and WMDP with six unlearning methods.
Coupled contest analysis finds TRACE can raise optimistic-rollup execution diversity more than Proof of Diligence.
On TRACE's 590 AppWorld boundaries, recent agent history only weakly predicts harmful context compaction.
TRACE aligns FP4 train and rollout paths for MoE RL, matching BF16 quality with up to 5.4x rollout speedup.
TRACE cut multi-turn attack success to the lowest rate in all 35 model-attack pairs with at most a 1.23-point utility drop.
TRACE benchmarks streaming video models on timing, triggers, workload, and reliability, not accuracy alone.
TRACE reconstructs private embodied observation-action trajectories from policy gradients, reaching 18.8 dB PSNR.
The Linux Foundation introduced TRACE, an open standard providing hardware-attested runtime and compliance evidence for AI agents.
The Linux Foundation adopts TRACE, an OPAQUE-contributed spec giving AI agents hardware-attested, cryptographically verifiable runtime and compliance evidence.
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