type stringclasses 2
values | harness stringclasses 1
value | id stringclasses 1
value | name stringclasses 1
value | message dict |
|---|---|---|---|---|
session | trackio | agent_run | Agent repro run 2026-08-03 03:37 UTC | null |
message | null | null | null | {
"role": "system",
"content": "Event",
"timestamp": 1785728255596
} |
message | null | null | null | {
"role": "assistant",
"content": "[Claim 0 — PI controller learns dynamic Top-p threshold]\n# Claim 0 — PI controller learns dynamic Top-p threshold\n\nEvidence.\n- Numbers from job `6a5ee27ad09dc1f57c6be6f6`:\n - Sparsity low: `0.5`\n - Sparsity high: `0.9`\n- Interpretation: simulated control trace shows thres... |
message | null | null | null | {
"role": "assistant",
"content": "[Claim 1 — Fixed Top-p matches Top-k MoE FLOPs]\n# Claim 1 — Fixed Top-p matches Top-k MoE FLOPs\n\nEvidence.\n- Numbers from job `6a5ee27ad09dc1f57c6be6f6`:\n - Fixed Top-p approximate active experts: `8`\n - Top-k baseline: `12`\n- A real expert-routing benchmark would be requ... |
message | null | null | null | {
"role": "assistant",
"content": "[Claim 2 — Strong scaling across expert granularity / capacity / model / dataset size]\n# Claim 2 — Strong scaling across expert granularity / capacity / model / dataset size\n\nEvidence.\n- Only a small control-theoretic proxy was run; scaling sweeps are not present.\n- Numbers f... |
message | null | null | null | {
"role": "assistant",
"content": "[hEvt3HWxD3 — DTop-p / dynamic MoE routing logbook]\n# hEvt3HWxD3 — DTop-p / dynamic MoE routing logbook\n\nScope: toy CPU proxy for PI-controller threshold learning.\n\nArtifact:\n- Job `6a5ee27ad09dc1f57c6be6f6` (COMPLETED): controller sparsity trace and fixed Top-p equivalent a... |
message | null | null | null | {
"role": "system",
"content": "Event",
"timestamp": 1785728255596
} |
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