cs.SEAug 18, 2026
SaveWhat Does an Evaluation License? A Commit-Bound Census of Claim Replay in Inspect Evals
Organizations: Wuhan University
Abstract
Benchmarks can run without determining what their results license. We freeze a large evaluation collection and attempt to replay its historical claims. Most units stop because the evidence required for replay is not bound. Where replay is possible, different claims remain stable at different resolutions. We make this otherwise implicit inference step explicit and executable.
Figures & tables
Figure 1: Three questions, three outputs. Missing evidence, multiple evaluator meanings, and disagreement across claim levels are not one generic robustness outcome.
| Reading | Family | Claude 3.5 | Gemini 2.0 | GPT-4o-mini |
|---|---|---|---|---|
| Published micro | Primary | 1.113 | 20.827 | 27.186 |
| All-run micro | Primary | 1.113 | 14.120 | 27.186 |
| Common-suite macro | Review only | 1.473 | 26.731 | 30.665 |
| Utility-conditional | Review only | 1.316 | 32.000 | 19.745 |
| Worst suite | Review only | 3.810 | 66.667 | 57.143 |
| Primary (2A): one winner; one full order; 3/3 pairs agree | ||||
Table 1: AgentDojo targeted attack success rate (lower is better) over the same outcomes. The primary analysis uses the first two readings; the review family also asks what happens under the three disputed readings.
| Evidence stream | Design | What it licenses |
|---|---|---|
| 124-unit census | Complete mechanically eligible frame at one commit | Within-frame accounting: 14 complete, 110 explicit stop records |
| Frozen random ten | Two per stratum; case selection frozen before terminal audit outcomes; outcome exposure recorded separately | Completion under that frozen balanced-strata draw: 3/10 |
| Mechanism portfolio | Three purposive deep audits plus eight labeled outcome-exposed discoveries | Examples of how claims agree or disagree, not a frequency |
Table 2: Three evidence streams and the statements they license.
| Native object | Already supports | What the historical claim still needs |
|---|---|---|
| task/scorer | Forward task and scoring definition | Historical instance and replay target |
| EvalLog , when retained | Inputs, outputs, targets, scores, metadata, reductions | Support decisions and admitted evaluator family |
| report | Metrics and reproducibility metadata | The claim being asked and the answers that agree or disagree |
Table 3: What native evaluation objects provide, and what a historical claim still needs.
| Stream / case | Evaluator choices | P/E winner or direction | P/E order / stable pairs |
|---|---|---|---|
| Random (3 complete) | credit, aggregation, claim target | all: non-id / non-id | all: non-id / non-id ; 0/1, 0/1, 0/3 in both |
| Purposive: AgentDojo | eligibility, denominator, aggregation | winner id / id | P: id , 3/3; E: non-id , 2/3 |
| Purposive: AutoML | missingness, task/rank aggregation | winner id / id | P: id , 10/10; E: non-id , 9/10 |
| Purposive: BEIR (5 views) | metric, cutoff, relevance grading | winner id / id | non-id / non-id ; 2/3 in both |
| Outcome-exposed exploratory (8) | source/evaluator readings and audit proposals | Case-specific landscape; no pooled P/E claim | |
Table 4: What stays fixed across evaluator meanings, separated by evidence stream. P/E denote the primary/review families . Detailed random and exploratory rows are in the appendix.
| Question | Available-case sensitivity summary | Claim-replay result |
|---|---|---|
| Can the claim be replayed? | Conditions on cases with usable observations or leaves missing cases outside the numerical analysis | Retains all 124 records; 110 receive an explicit stop with the first missing item and minimum unblock |
| Which choices define the claim? | May pool all executable variants into one choice set | Separates the primary family from the wider review family; AgentDojo and AutoML have one primary order but multiple review-family orders |
| What survives variation? | Often reports a scalar range or any flip | Reports claim-specific answer sets, witnesses, and stable relations; the BEIR sensitivity shows that 2/3 stable pairs over five views can become 0/3 over an expanded evaluator grid |
Table 5: What an available-case sensitivity summary can lose, and what claim replay adds.
Figure 2: What the added interface changes. It preserves cases that cannot be replayed, separates primary from disputed meanings, and states what remains fixed alongside what changes.
Figure 3: One rule changes the conclusion while predictions stay fixed. Left: replacing the original one-sided terminal rule with either symmetric rule moves the adoption effect from approximately pp to zero. Right: the exclude-both family still permits five weak orders, yet Mini is the unique winner.
Appendix figures & tables32 assets
Supplementary material from the paper’s appendix.
Appendix
Figure 4: Four coordinates that a scalar sensitivity range can conflate. The present contract enumerates semantic variation on fixed evidence, keeps sampling uncertainty separate, and removes purely reversible representation changes before claim comparison.
| Layer | What is checked | Licensed conclusion |
|---|---|---|
| Mechanical closure | Hashes and schema; terminal accounting; deterministic source-table recomputation; family projection; claim images, witnesses, and stable pairs | The bound bytes produce the reported arithmetic and identified sets through an independently checked code path |
| Human-auditable semantic provenance | Source locators and quotations; normalized authorization; same-target/support rationale; A/D/X judgments; evidence horizon | An independent reader can inspect, dispute, and correct the semantic ledger; the automated verifier does not prove construct validity or provenance correctness |
| Outside both layers | Unreleased sample-level facts; unenumerated semantics; future releases or interventions | No family-completeness, ecosystem-prevalence, independent-replication, benchmark-validity, causal-utility, or future-stop-reduction claim |
Table 6: Two validation layers and their distinct licenses.
| View | Complete | stop | Licensed interpretation |
|---|---|---|---|
| All 124 | 14 | 110 | Terminal auditability inside the complete eligible frame |
| Outcome-blind census-review path (114) | 11 | 103 | Source review, admission, and fixed-observation execution before outcome inspection |
| Frozen random ten | 3 | 7 | Completion under the balanced two-per-stratum draw; stopped units retained |
Table 7: Nested accounting for the commit-bound frame. The rows are accounting views, not pooled result samples.
Figure 5: Two accounting axes. The top line exhausts the 124-unit frame. The bottom line names evidence panels with distinct selection and exposure licenses; arithmetic equality does not make them one cohort.
Figure 6: The preservation chain is claim-relative. A retained scorer is only the first layer; later claims can require historical outputs, mediator decisions, state, support joins, and an admitted semantic registry. The preservation layers are conceptual dependencies; the verifier precedence used for first-stop accounting is G1–G8 below.
| Layer | Required object | Enables | Typed stop when absent |
|---|---|---|---|
| Source | task, scorer, registry revision, dependencies | Ground candidate formulas | source/evaluator binding |
| Observation | sample-keyed outputs and system/prompt binding | Apply alternatives to the same responses | comparative observations |
| Mediator/state | judge decisions or sufficient terminal state | Replay mediated or stateful endpoints | judge trace or execution state |
| Support | keys, DNF/missingness masks, denominators | Compare without silent eligibility change | support or missingness |
| Semantic registry | endpoint type, origin/admission, same target/support, units/ties | Form | family or claim review |
Table 8: Preservation layers required by claim replay.
| Reader label | Count | First unavailable requirement |
|---|---|---|
| Evidence binding | 47 | Source or observation bytes could not be jointly bound |
| Comparative observations | 35 | Fixed outputs for a common system/support set were absent |
| Judge trace | 9 | Responses, judge binding, and decisions were not jointly frozen |
| Endpoint type | 4 | Available outputs lacked a shared typed endpoint |
| Semantic target | 4 | Candidate metrics addressed different targets |
| Missingness / DNF | 2 | Missing outcomes lacked a declared non-ignorable rule |
Table 9: Primary stopping codes for the 103 stops on the outcome-blind 114-case path.
Figure 7: First unavailable requirement among the 103 stops on the outcome-blind 114-case path. The distribution identifies release-interface bottlenecks; it is not a benchmark-quality score and not evidence of intervention utility.
Figure 8: Claim resolution across the six complete audits. P/E denote primary/review scopes. The last column reports stable pair counts. AgentDojo and AutoML make the admission effect visible: their primary orders are identified even though their review-envelope orders are not. The BEIR row is scoped to its declared five-view family; the separate 25-view coverage sensitivity is reported below.
Figure 9: Stable-backbone retention across declared complete-audit families. Bar length is the fraction of system pairs whose relation is invariant; labels give exact stable/total counts. The BEIR bar is 2/3 over the declared five views, not an evaluator-wide claim: its 25-view sensitivity yields 0/3.
| Case | Audit intervention | Claim effect | Licensed lesson |
|---|---|---|---|
| AutoML | Reclassify average task rank from AP/D to SM/A after binding the canonical missing-value, fold, task-rank, and average-rank procedure | Ledger changes from 3A+2D to 4A+1D; winner, order image, 10/10 primary pairs, and 9/10 envelope pairs are unchanged | Provenance can be corrected without destabilizing inference |
| BEIR SciFact | Retain the declared five views, then separately expand to all 25 evaluator-exposed metric–cutoff cells executable from the top-100 runs | Winner ID NID; order remains NID but expands to five weak orders; backbone 2/3 0/3 | Mechanically correct arithmetic does not license transport beyond the named family |
Table 10: Provenance correction and family expansion are different perturbations.
| Case | Perturbation | Winner after perturbation | Complete-order consequence |
|---|---|---|---|
| AgentDojo | common-key suite-macro ASR, D A alone | Claude 3.5 Sonnet | ID; primary order unchanged |
| AgentDojo | utility-conditional ASR, D A alone | Claude 3.5 Sonnet | NID; GPT-4o-mini/Gemini pair reverses |
| AgentDojo | worst-suite ASR, D A alone | Claude 3.5 Sonnet | NID; GPT-4o-mini/Gemini pair reverses |
| AutoML | worst-task AUC, D A alone | H2OAutoML | NID; AutoWEKA/TPOT pair reverses |
| BEIR SciFact | No D candidate; five 25 is a coverage, not admission, perturbation | Non-identified | NID; all three pairs become unstable |
Table 11: One-at-a-time boundary perturbations propagated through the claim calculation.
| Packet | Intact | Source | Claim | Endpoint | Observations |
|---|---|---|---|---|---|
| ComputeEval (021) | COMPLETE | G1 STOP | G2 STOP | G3 STOP | G4 STOP |
| MLRC-Bench (043) | COMPLETE | G1 STOP | G2 STOP | G3 STOP | G4 STOP |
| TAC (086) | COMPLETE | G1 STOP | G2 STOP | G3 STOP | G4 STOP |
| UCCB (101) | COMPLETE | G1 STOP | G2 STOP | G3 STOP | G4 STOP |
| Pre-Flight (105) | COMPLETE | G1 STOP | G2 STOP | G3 STOP | G4 STOP |
Table 12: Controlled evidence-ablation conformance. Cells report the replay terminal after the named single-class deletion.
| Case | Design | Winner P/E | Order P/E | Pairs P/E |
|---|---|---|---|---|
| TheAgentCompany | random complete | NID/NID | NID/NID | 0/1 0/1 |
| BBEH | random complete | NID/NID | NID/NID | 0/1 0/1 |
| Personality | random complete | NID/NID | NID/NID | 0/3 0/3 |
| AgentDojo | purposive | ID/ID | ID/NID | 3/3 2/3 |
| AutoML | purposive | ID/ID | ID/NID | 10/10 9/10 |
| BEIR SciFact | purposive | ID/ID | NID/NID | 2/3 2/3 |
Table 13: Claim-relative family stress. P/E denote primary/review; pair entries are stable/total.
| Cohort | Object | Controlling audit outcome |
|---|---|---|
| Random 10 | GDM InterCode CTF | stopped after semantic candidates: comparative observation absent |
| Random 10 | TheAgentCompany | complete finite-family audit |
| Random 10 | FrontierScience | stopped after semantic candidates: model judge trace absent |
| Random 10 | BBEH | complete finite-family audit |
| Random 10 | Agent Bench | stopped after semantic candidates: stateful execution artifact absent |
| Random 10 | CORE-Bench | stopped after semantic candidates: stateful execution artifact absent |
| System/artifact | Specification output | Exact reconstructed value |
|---|---|---|
| inspect_haiku45 | any_progress | 0.6176470588235294 |
| inspect_haiku45 | mean_checkpoint | 0.36264705882352943 |
| inspect_haiku45 | strict_completion | 0.11764705882352941 |
| original_sonnet4 | any_progress | 0.47058823529411764 |
| original_sonnet4 | mean_checkpoint | 0.2164705882352941 |
| original_sonnet4 | strict_completion | 0.14705882352941177 |
| System/artifact | Specification output | Exact reconstructed value |
|---|---|---|
| inspect_reproduction | harmonic_no_pseudocount | 0.0425272071389958 |
| inspect_reproduction | harmonic_plus_0_01 | 0.07898405712442381 |
| inspect_reproduction | sample_micro | 0.2150442477876106 |
| inspect_reproduction | task_macro_arithmetic | 0.22086956521739132 |
| original_paper | harmonic_no_pseudocount | 0.0 |
| original_paper | harmonic_plus_0_01 | 0.060462587043807435 |
| System/artifact | Specification output | Exact reconstructed value |
|---|---|---|
| claude3_opus | negative_mae_all8 | -4.825000000000001 |
| claude3_opus | negative_mae_big5 | -7.300000000000002 |
| claude3_opus | negative_rmse_all8 | -6.252199612936236 |
| claude3_opus | pairwise_rank_agreement_all8 | 1.0 |
| claude3_opus | pearson_all8 | 0.9977220344447256 |
| gpt35_turbo | negative_mae_all8 | -4.04125 |
| Case | Compared readings | Candidate status | Claim resolution | Boundary |
|---|---|---|---|---|
| VQA-RAD | overall micro vs equal closed/open macro | second aggregation audit-proposed | exact non-id ; winner/order id ; 1/1 stable | source does not declare equal answer-type overall |
| MORU | sample-first overall vs equal 16-dimension macro | second aggregation audit-proposed | exact non-id ; winner id ; order non-id ; 9/10 stable | dimension vector exposed; second overall not declared |
| InstrumentalEval | prompt-global vs equal six-type macro | second aggregation audit-proposed | single-system exact non-id | per-type metrics do not declare a second overall |
| ANIMA | historical overall vs dimension-normalised average | both source-declared | exact non-id ; winner id ; order non-id ; 5/6 stable | table-level reconstruction at displayed precision |
| AIR Bench | item-micro vs equal-category macro delta | second aggregation audit-proposed | exact delta non-id ; direction id | category rows do not declare a macro headline |
| LiveBench | subtask–category vs item–category macro | both source/evaluator-exposed | exact non-id ; winner/order id ; 1/1 stable | historical aggregates and displayed precision only |
Table 18: Claim-resolution profile for eight exploratory cases.
Figure 10: Mechanism map for the eight exploratory cases. Position is a qualitative routing summary, not a statistical embedding. It separates harmless representation changes, exact-value sensitivity, lower-order changes, and the BFCL support-limited winner candidate.
| System | Sample-first | Equal 16-dimension macro |
|---|---|---|
| GPT-5.2 | (421/500) | (12593/16000) |
| GPT-5-mini | (102/125) | (3117/4000) |
| Claude Haiku 4.5 | (37/50) | (11413/16000) |
| Gemini 2.5 Flash Lite | (713/1000) | (2157/3200) |
| Grok 4.1 Fast | (711/1000) | (5407/8000) |
Table 19: MORU exact rational reconstruction; the equal-dimension macro is audit-proposed.
| System | Historical overall | Dimension-normalised |
|---|---|---|
| Claude Haiku 4.5 | (639/1000) | (8009/13000) |
| Gemini 2.5 Flash Lite | (161/250) | (3971/6500) |
| Grok 4 Fast | (17/25) | (8821/13000) |
| GPT-5-mini | (391/500) | (9681/13000) |
Table 20: ANIMA table-level reconstruction; both columns are source-declared.
| System | Count-weighted micro | Equal ten-group macro |
|---|---|---|
| Claude Haiku 4.5 | (16701/20600) | (5767/7500) |
| GPT-4.1-mini | (225821/283250) | (11639/15000) |
Table 21: BFCL calculation on the 3,399-item published-category subset.
Figure 11: Independent recomputation localizes each order change. MORU and ANIMA preserve the winner and change one lower pair; BFCL changes the only pair but remains a support-limited exploratory result.
| Group | Required content |
|---|---|
| Claim and substrate | case/query identifiers; endpoint type, orientation, unit, tie rule; systems and common observation/support keys; scorer, judge, or state binding |
| Candidate ledger | formula or implementation; variation layer; origin; reliability result; A/D/X admission and rationale; same-target/support decision |
| Aggregation and support | denominator and aggregation tree; missingness/DNF rule; weights; unit transform; declared support changes |
| Exposure and freeze | evidence horizon; pre-outcome ledger digest; exposure state; append-only amendments |
| Output or stop | primary/review values, top sets, weak orders, pair relations, witnesses; otherwise stop stage, missing object, no-imputation rationale, and minimum unblock |
Table 22: Minimal field groups for an executable claim-identification record.
Figure 12: Executable contract. Human judgment fixes type and admission before this state machine. Thereafter both family projection and identified-set enumeration are deterministic; a missing critical binding exits through a typed stop.
Figure 13: The prospective question is deliberately separate. The present paper supplies the intervention targets and measurement contract; it does not claim the three future endpoints.
Figure 14: Controlled diagnostic specifications. Object contract, disposition policy, and terminal semantics index the downstream endpoint. Sampling precision inside one box does not integrate over an omitted semantic coordinate.
| Disposition | Original asymmetric | Retain both | Exclude both | Aggregate symmetric minus original |
|---|---|---|---|---|
| Empty/empty credit | ||||
| Empty no credit | ||||
| Conditional nonempty |
Table 23: Task-disjoint adoption effects and frozen 95% task-cluster percentile intervals, in percentage points.
Figure 15: Controlled result: effect typing and ranking structure separate. Panel A shows that symmetric terminal handling collapses the contrast-comparable effect to zero. Panel B shows that complete rankings can remain non-identified while a unique winner or stable relations survive.
| Treatment | PageRank–Earliest intervals | Weak orders | Reversal pairs | Kendall | Possible winners |
|---|---|---|---|---|---|
| Retain both | 3 | 1 | 5 | ||
| Exclude both | 5 | 6 | 1 |
Table 24: Task-disjoint ranking summaries under contrast-comparable terminal treatments.
| Policy | Average effect (95% CI) | Interpretation |
|---|---|---|
| Empty/empty credit | Fixed 217-row total-score estimand; cellwise crossing | |
| Empty no credit | Same rows and denominator; crossing removed | |
| Conditional nonempty | Narrower support and different endpoint |
Table 25: Empty-family semantics on fixed or explicitly narrowed support.
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