D2ACCI introduces a dual-loop diagnostic protocol that localizes memory failures to specific pipeline stages, raising diagnostic success from 0% to 98–100%; Salesforce re-evaluates memory-based self-improving agents and finds that shuffling task order turns an expected +1.5% gain into a -4.5% drop; GraphWake shows that poisoning just 10% of agents' memories can drastically amplify group opinion polarization
ActBench red-teams cowork agents via execution traces, finding ASR of 73.7%–94.4% even when swapping harnesses; Agent Behavioral Contracts II shows co-failure rates hit 90% for same-model two-stage pipelines, breaking the conditional independence assumption; Graph-Based RL Drift Diagnosis uses a small-model recovery graph to detect drift and auto-rollback without retraining the primary agent
Harness-IF reveals Coding Agent instruction following is overestimated by 3.6-7.4 pp because things the model would do anyway are counted as compliance; SHE decomposes the harness into four safety components and auto-evolves from trajectory failures, cutting ASR by 3.1x while improving correctness; SBCO uses a decomposed verifier bank with text gradients for harness self-improvement, matching Gödel Machine at 4-5.5x lower compute on planning tasks
Tool interface design boosts coding agent consistency by 4.7x while halving token usage; memory distillation lifts a 4B model's AppWorld accuracy by 27.2 percentage points to near-frontier level; institutional design experiments show that identical safety rules paired with different enforcement mechanisms yield violation rates ranging from 0% to 23%
Evo-Bench benchmarks nine models on self-improving harnesses — GPT-5.6 Sol tops at +16.6 but Office tasks barely move; MEGA uses a three-layer Wisdom Graph to make agent optimization infrastructure self-evolving, merging knowledge accumulation with optimization; SHE decomposes harnesses into four evolvable components that learn safety boundaries from failure trajectories, cutting ASR by 3.1x with cross-model transferability
VerMem's seven atomic memory operations plus dual verifiers lead all baselines by 5-8 points across five benchmarks; SafeCommit cuts unsafe action rate from 41.2% to 2.6% while maintaining 97.4% task completion; ToolLIFT abstracts tool trajectories into function-level workflow graphs, outperforming the strongest baseline by 3-5 points on OOD benchmarks