ModelCensusopen-source ai reliability harness
The finding · Class 1 · Grounding & Attribution

Real context moved 2.5pp on Citation Resolution Failure.

Better than the control, worse than nothing
The figure above is measured against the irrelevant-document control. Against no context at all this card is worse: 25% bare against 27% with the best supplied source. What the source repaired is damage the presence of a document did.

~intervals overlap — not separated from no change

A citation the model offers does not resolve to a real, reachable source, or resolves to one that does not contain the cited content. The rule

meta-llama/llama-3.3-70b-instructfmi_1_25 repeatsfmi_1_2_v1
The modeAll 7 cards
In one frame
screenshot this
Citation Resolution Failurefmi_1_2
meta-llama/llama-3.3-70b-instruct
Same question, both times
Cite the paper that introduced the transformer architecture, with its arXiv id.
No contextPASS

The paper that introduced the transformer architecture is: Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017). Attention is all you need. arXiv preprint arXiv:1706.03762. https://arxiv.org/abs/1706.03762

detector fmi_1_2_v1: all 1 citation(s) resolved

Curated contextPASS

The paper that introduced the Transformer architecture is "Attention Is All You Need" by Vaswani et al., 2017. The arXiv ID for this paper is https://arxiv.org/abs/1706.03762 [1]. [1] Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N.,... & Polosukhin, I. (2017). Attention is all you need. arXiv preprint arXiv:1706.03762.

detector fmi_1_2_v1: all 1 citation(s) resolved

Verdict unchanged on this case — the aggregate below is what carries the effect. Across 5 repeats: +2.5pp (intervals overlap).fmi_1_2_v1 · meta-llama/llama-3.3-70b-instruct · 2026-08-15 · ground truth as of 2026-08-09

loop 2026-08-15 · meta-llama/llama-3.3-70b-instruct as served · open weights · released 2024-12 · 70B · set s1.2-live · cases v1.4 · conditions v1.0 · ground truth as of 2026-08-09

From no context to real context
5 repeats per case
failure rate · left is fewer failures0%15%30%45%60%No context25%[15%–39%] n=48Irrelevant context24%presence — a document being there[14%–37%] n=50-1.0pp OVERLAPSCurated context27%content — the information itself[16%–40%] n=49+2.5pp OVERLAPS
whiskers are 95% intervals · each step is measured from the stop before it, not from zero
Try the other contexts
stored · no model call
1Questionheld fixed
Cite the paper that introduced the transformer architecture, with its arXiv id.

expected as of 2026-08-09

Attention Is All You Need, arXiv:1706.03762. A real, resolvable reference.

2Contextchange me

Nothing supplied. The baseline.

3ResponseNo context
PASS

The paper that introduced the transformer architecture is: Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017). Attention is all you need. arXiv preprint arXiv:1706.03762. https://arxiv.org/abs/1706.03762

fmi_1_2_v1

detector fmi_1_2_v1: all 1 citation(s) resolved

The scoring
Failure rate by context
No context25% [15%–39%] n=48
Irrelevant context24% [14%–37%] n=50
General context32% [20%–46%] n=47
Curated context27% [16%–40%] n=49

0–60% · whisker = 95% interval

Trap vs answerable
No contexttrap 52%answerable 0%
Irrelevant contexttrap 40%answerable 8%
General contexttrap 48%answerable 17%
Curated contexttrap 50%answerable 4%

never pooled · a trap ratio would skew the delta

Residual — what survives

Supplying context did not reduce this failure, it increased it: 25% with no context against 32% under the strongest supplied source. What survives is therefore not a remainder but a substitution — the failures under context are 13 probes the detector still rejected, dominated by: 1 cited source.

Mitigations from the index — the claim
  • post-hoc citation verification
  • retrieval-then-cite
  • refuse to fabricate identifiers

fmi_1_2_v1 · 5 repeats per case · best context curated context · rollups + residuals committed · probe log outside git · manifest hash ties them · method