tracea-explainer β€” trace β†’ plain-English behavior reports (planned)

🚧 Status: adapter training scheduled for Week 4 (target: Nov 10, 2026). This card will be updated with metrics, samples, and the adapter download when training completes on TraceBench.

A LoRA adapter for Qwen3-4B-Instruct that reads Evidence Record v1 streams produced by tracea (hooks, syscall summaries, HTTP/TLS/DNS evidence) and writes a grounded plain-English behavior report β€” every claim tied to an evidence record.

Why

Agents trace software, but raw evidence is verbose and easy to misread. tracea-explainer is the "narrator": it turns structured runtime evidence into human/agent-readable reports without inventing claims β€” trained to abstain when evidence doesn't support a statement (the "limitations" discipline of Evidence Records).

Training plan

Item Value
Base Qwen/Qwen3-4B-Instruct
Data TraceBench train split (trace JSONL β†’ narrative)
Method LoRA (r=16, Ξ±=32), bf16, seq len 8k
Eval held-out scenarios; factuality vs. ground truth; abstention rate
Serving vLLM/llama.cpp; wired into the tracea-demo Space "Auto-explain" tab

Intended use

  • Narrating authorized dynamic-analysis sessions (your apps, devices, captures)
  • Security education, debug triage summaries, agent report generation

Out of scope

Closed-source targets without authorization; malware development; DRM circumvention.

Links

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