Research / Absorption Log
Every day a pipeline pulls the curated papers of the day, triages them against the ten research domains I actively work in, and issues one of five verdicts. The rule that keeps it honest: a verdict without a named system, a defined test, or a falsifiable claim is invalid. This log is the public record.
This status is published even when no new verdict is produced. It keeps the automation honest: pending queues, due state, last absorb time, and report count are visible instead of being hidden behind the latest successful report.
Pending papers
57
Pending queues
4
Reports
1
2026-06-09
12 papers
Skill-RM: Unifying Heterogeneous Evaluation Criteria via Agent Skill
arXiv:2606.039802026-06-11
12 papers
Claw-SWE-Bench: A Benchmark for Evaluating OpenClaw-style Agent Harnesses on Coding Tasks
arXiv:2606.12344Experiment queue
ABSORB and TEST verdicts are converted into experiment packets. This is the handoff point from reading to implementation: baseline, action, success metric, and required evidence.
Internal baseline: evoflow MCP / TIE workflows
Claim: execution-grounded workflow repair beats SFT/RL under low trace budgets (3%->17-24% MCP-Bench)
Task: Implement and measure the absorption against the named counterpart.
Define pass/fail before implementation; report no-effect if the internal baseline does not improve.
Internal baseline: KARL reward_engine.py
Claim: outcome-only grading overestimates; trajectory-integrity judging is the fix
Task: Implement and measure the absorption against the named counterpart.
also future TEST target (114 tasks, frontier PassRate 41.2%)
Internal baseline: deterministic harness thesis (Claude Code + chains + ELP-2)
Claim: learned controller matches hand-engineered harnesses on Terminal-Bench 2.0 / SWE-bench Verified
Task: Run a head-to-head comparison against the current internal baseline.
Define pass/fail before implementation; report no-effect if the internal baseline does not improve.
Trigger: KARL moves to per-step credit assignment -> lift their step-wise reward decomposition
Trigger: 3rd strong env-engineering result
Trigger: mesh message bandwidth becomes bottleneck
Claim: keyword collision; medical domain, no counterpart
Trigger: formalizing deep-research evals
Claim: learned controller matches hand-engineered harnesses on Terminal-Bench 2.0 / SWE-bench Verified
Action: run our deterministic stack on Terminal-Bench 2.0; metrics: pass rate, tokens/task, trajectory length; win = match without training
Claim: execution-grounded workflow repair beats SFT/RL under low trace budgets (3%->17-24% MCP-Bench)
Action: add execution-feedback mutation loop to evoflow workflow engine using their typed operator set
Trigger: next cognitive-forge data round -> adopt shortcut-resistance filters
Trigger: KARL adds online RL
Claim: outcome-only grading overestimates; trajectory-integrity judging is the fix
Action: add W_INTEGRITY 7th signal to compute_reward(): penalize outcomes lacking corroborating artifacts
Trigger: also future TEST target (114 tasks, frontier PassRate 41.2%)
Claim: no system of ours in this lane
Claim: no counterpart
12 verdicts logged · updated 2026-06-13