ChrisRPL/blackline-atlas-lfm25-vl-sft-hf-corpus-full-v1b-adapter

Blackline Atlas LFM2.5-VL Adapter

This is the final public Blackline Atlas Liquid-track adapter for the hackathon submission. It is a PEFT/LoRA adapter for LiquidAI/LFM2.5-VL-450M.

Intended Role

The adapter is a guarded visual site-brief component. It compares a selected Sentinel/SimSat baseline image and current image, then writes a structured civilian-scope brief:

• visible scene
• likely visual change
• limitations such as cloud, low resolution, or no-data tiles
• relationship between the source report and what is actually visible
• one of discard, defer, or downlink_now

It is not autonomous alert authority. Blackline Atlas keeps final triage under deterministic civilian guardrails and fails closed when model output is invalid.

Training Data

Dataset: ChrisRPL/blackline-atlas-training-corpus-v1

The corpus contains normalized, license-aware training shards for source-led satellite triage. It is not a raw mirror of third-party datasets. It includes planner/tool rows, paired-image visual brief rows, hard negatives, and SimSat/Sentinel examples with provenance/audit notes.

Training split: 30,858 rows. Eval split: 3,421 rows.

Training job: 69f66f889d85bec4d76f0be0

Objective

Supervised fine-tuning for structured visual brief generation over civilian infrastructure disruption examples. The model is trained to separate source facts from satellite-visible facts and to prefer low-confidence discard/defer when imagery is cloudy, low resolution, or not directly evidentiary.

Evaluation Summary

• Eval loss improved from 3.0021 to 0.3273.
• Corpus-native 22-case SimSat gold eval:
  • 22 / 22 valid JSON outputs
  • 19 / 22 analyst-schema valid reports
  • 9 / 22 action matches

These results support a guarded analyst-narration lane. They do not justify autonomous alerting.

Runtime Use

Blackline Atlas uses this adapter after a source lead resolves to Sentinel current/baseline imagery. Contact sheets may be supplied as orientation-only context. Mapbox tiles are not evidence. SAM/SAM3 masks are not part of the judge runtime path for low-resolution Sentinel pairs.

Expected JSON actions:

• discard
• defer
• downlink_now

Malformed, tactical, source-only, or low-confidence output should be repaired only when safe; otherwise it is withheld.

Safety Boundary

Allowed use: civilian resilience, humanitarian logistics transparency, public accountability, and macro-scale disruption triage.

Disallowed use: tactical targeting, strike support, military asset ranking, troop/convoy tracking, sabotage guidance, or claims of real-time surveillance beyond the source data and satellite imagery.

This adapter is not autonomous alert authority and should not be used as a sole decision-maker for emergency, military, law-enforcement, or targeting decisions.

Limitations

• Sentinel imagery may be cloudy, low resolution, stale, or missing.
• The model can overstate source facts if not guarded; runtime code strips or withholds source-only casualty/impact claims.
• Action match is not strong enough for autonomous scoring.
• Satellite-visible evidence is macro-scale only. Tiny objects and tactical interpretations are out of scope.