JEPA-Like E1/E2 Representation Reference Contract
Claim Type: implementation_note
Scope: Interface contract for using JEPA-like world-model patterns as E1/E2 representational reference architecture (JEPA project remains external)
Depends On: IMPL-020, IMPL-021, ARC-001, ARC-002, ARC-005, ARC-015, MECH-057
Status: stable
Claim ID: IMPL-022
Purpose
Specify how JEPA-like patterns can be integrated into REE as representational references for:
E1deep predictive representation path (slow, coherence-preserving latent structure),E2fast predictive representation path (short-horizon transition prediction).
This contract isolates the representation boundary so control-completion behavior remains explicit REE scope.
Decoupling declaration:
- JEPA is an external project and not a component of REE.
- REE may use JEPA-like representational patterns as reference points for E1/E2 interfaces.
- JEPA is not treated as REE substrate ownership.
- JEPA cannot carry E3 commitment, responsibility attribution, or control-plane authority semantics.
Canonical boundary note:
- this document defines the REE-side integration contract only,
- source-specific JEPA integration playbooks, exploratory mappings, and probe planning live in
REE_convergence(sources/jepa/*) and enter here only via convergence packets.
Functional mapping note:
E1andE2should be treated as functional decomposition over JEPA-like reference streams, not necessarily separate physical modules.- Fast online predictor adaptation can realize
E2behavior. - Slow target/anchor dynamics and continuity constraints can realize
E1behavior. - The required separations are update-rate asymmetry, typed routing, and write-locus permissions, not total latent isolation.
Integration Boundary
Reference-profile side provides:
- latent state encoding,
- latent future prediction,
- optional action-conditioned latent dynamics.
REE side retains ownership of:
- commitment gating (
E3), - control-plane arbitration and precision routing,
- responsibility attribution/efference-reafference learning,
- residue and viability constraints.
Required Interface Surfaces
Inputs into JEPA-like reference adapter
obs_t: current observation slice.ctx_{t-k:t}: context window (optional memory-conditioned input).a_t(optional): candidate action token/vector for action-conditioned predictions.mode_tags(optional): REE regime hints (deliberative,reactive,reflective) for evaluation-only stratification.
Outputs from JEPA-like reference adapter
z_t: latent representation for current context.z_hat_{t+1:t+h}: predicted latent futures for horizonh.pe_latent: latent prediction deviation statistics (L-state deviation).uncertainty_latent(optional): calibrated uncertainty/dispersion estimate over latent predictions.
JEPA-inspired signal map (adapter contract)
The adapter must map native JEPA training/runtime streams onto stable REE-facing keys:
| REE contract key | JEPA-native stream | Extraction rule | Status |
|---|---|---|---|
z_t | encoder/target-encoder latent tokens | export post-normalization latent for the active context window | direct |
z_hat_{t+1:t+h} | predictor output tokens | export predictor outputs aligned to masked target blocks and rollout step index | direct |
pe_latent.mean | latent prediction loss | compute mean latent distance from z_hat to target latent (smooth_l1/equivalent) | direct |
pe_latent.p95 | latent prediction residuals | compute p95 over per-token latent residuals before global reduction | derived |
pe_latent.by_mask | masked block residuals | emit per-target-mask residual mean keyed by mask id | derived |
uncertainty_latent.dispersion | multi-target/multi-step latent spread | estimate dispersion across equivalent target predictions (same context, multiple masks/seeds) | derived |
uncertainty_latent.calibration_error | predicted uncertainty vs realized residual | expected calibration error between uncertainty estimate and realized pe_latent bins | derived |
trace.context_mask_ids | mask sampler outputs | emit exact context/target mask ids used for each prediction | direct |
trace.action_token (if action-conditioned) | action-conditioned predictor input | emit action token/vector hash + schema id for each rollout step | direct |
Notes:
pe_latentis already explicit in canonical JEPA implementations.uncertainty_latentis partially implicit in canonical JEPA and must be adapter-derived unless the producer exposes a dedicated uncertainty head.precision_latentis not guaranteed as an explicit calibrated JEPA output channel. The adapter may export internal precision proxies (for example, dispersion, ensemble disagreement, attention entropy, or action sensitivity) with provenance metadata; REE control-plane logic must compose the final confidence channel (uncertainty-derived precision).- Machine-readable adapter declaration for experiment packs:
evidence/experiments/schemas/v1/jepa_adapter_signals.v1.json.
JEPA↔REE control signal mapping matrix (execution contract)
This table defines ownership and gating for control-plane-relevant channels when a JEPA-like reference profile backs E1/E2.
| REE control function | REE-facing channel | JEPA source class | JEPA extraction examples | Final transform owner | Required checks | Canonical failure signatures |
|---|---|---|---|---|---|---|
Representation mismatch feed (MECH-058) | pe_latent | explicit/derived | smooth_l1 residual, p95, by_mask | REE consumes; adapter exports only | latent_residual_coverage_rate >= 0.95 | contract:jepa_residual_stream_missing, mech058:timescale_separation_collapse |
Confidence-channel synthesis (MECH-059) | confidence_channel | derived proxy bank | uncertainty_latent.dispersion, ensemble disagreement, attention entropy, rollout inconsistency, action sensitivity | REE control plane only | calibration, separability, and completeness checks | mech059:calibration_slope_break, mech059:uncertainty_metric_gaming_detected, mech059:abstention_reliability_collapse |
Pre-commit planning signal (MECH-060) | pre_commit_error | hybrid | pe_latent + hypothetical action-conditioned rollout deltas | REE control plane only | pre_commit_error_signal_to_noise and leakage checks | mech060:precommit_channel_contamination |
Post-commit attribution signal (MECH-060) | post_commit_error | hybrid | realized residuals + reafference delta + action trace | REE attribution path | post_commit_error_attribution_gain and attribution reliability checks | mech060:postcommit_channel_contamination, mech060:attribution_reliability_break |
Trajectory-first control support (MECH-056) | trajectory_candidate_risk | derived | rollout consistency + commitment reversal diagnostics | REE commitment layer | trajectory-first checks under ablation | mech056:trajectory_order_violation |
Channel-isolation guard (MECH-060) | cross_channel_leakage_rate | REE diagnostic | control-plane leakage estimator across pre/post channels | REE control plane only | cross_channel_leakage_rate <= threshold | mech060:cross_channel_leakage_spike |
Proxy bank declaration (adapter to control handoff)
When a JEPA-inspired control-routing profile is enabled, the adapter should export proxy_bank declarations for each active internal proxy used by REE confidence/channel logic. Each proxy entry should include:
proxy_id: stable key (uncertainty_dispersion,ensemble_disagreement,attention_entropy,rollout_inconsistency,action_sensitivity,other)source_stream: source family (uncertainty_dispersion/ensemble_disagreement/attention_entropy/rollout_inconsistency/action_sensitivity/other)extraction_method: short deterministic description of how the proxy is computednormalization: scaling/bounding transformwindow: temporal/statistical window usedcalibration_target: what the proxy is calibrated against (latent_residual,commitment_reversal,attribution_gain,other)provenance: adapter-internal source pointer (module name, tensor path, or equivalent)
Contract invariants
- Output latents must remain numerically stable under repeated rollout calls.
- Prediction deviation keys must be fixed-name numeric fields across runs.
- JEPA-like adapter outputs must not directly commit actions; they are advisory inputs to REE control.
- JEPA-like adapters may emit proxy signals, but must not emit final control-plane decisions or commitment actions.
Mapping Rules
z_tfeeds REEL-spaceingest path.- Multi-step
z_hatfeedsE2short-horizon prediction interfaces and hippocampal rollout seeding. pe_latentfeeds REE prediction-error routing (precision/eligibility inputs), not direct policy rewrite.- Any action-conditioned JEPA-like output is treated as hypothetical until E3 commitment.
- Internal JEPA-like proxies are valid control inputs only after explicit REE-side calibration and attribution-safe routing.
- Shared latent producers are acceptable if E1/E2 contractual roles remain distinguishable by update-rate and routing policy.
Signed PE and precision routing bridge
To keep representation/control separation explicit:
- JEPA-like adapter emits unsigned latent deviation and uncertainty streams only.
- REE computes signed decomposition downstream (for example, harm/benefit directional channels) using claim-owned control-plane rules.
- Precision routing consumes
pe_latent+ the confidence channel (derived from calibrated proxy bank inputs such asuncertainty_latent) + context tags; it is not learned implicitly inside the JEPA-like adapter.
Practical interpretation:
- A JEPA-like reference profile gives the mismatch stream (
what was wrong) and can expose dispersion (how many futures looked plausible). - REE converts that into a confidence channel (uncertainty-derived precision:
how strongly to trust this error for control) with explicit, auditable transforms.
Required Knobs (Config Contract)
The representation adapter must expose, at minimum:
latent_dimprediction_horizoncontext_windowaction_conditioned(bool)uncertainty_head(bool)update_rate_e1_proxy(slow path)update_rate_e2_proxy(fast path)-
residual_export_mode(global_onlyper_maskper_token) -
uncertainty_estimator(nonedispersionensemblehead)
REE-side control knobs remain out-of-scope for JEPA-like reference adapters and must be separately configured in control-plane docs.
Evaluation Contract
Required metrics (stable keys)
latent_prediction_error_meanlatent_prediction_error_p95latent_rollout_consistency_ratelatent_uncertainty_calibration_error(if uncertainty head present)action_conditioned_delta_error(if action-conditioned enabled)latent_residual_coverage_rate(fraction of predictions with exported residual trace)precision_input_completeness_rate(fraction of steps with all required PE/uncertainty fields)
Additional required metrics (JEPA-like control-proxy routing profiles)
proxy_bank_coverage_rate(fraction of steps with declared proxy provenance)proxy_confidence_calibration_ece(confidence-channel calibration error from proxy-driven confidence)proxy_residual_correlation_abs(absolute correlation between confidence channel and raw residual magnitude)proxy_ablation_control_delta(control quality delta when proxy bank is disabled vs enabled)
Required checks
- separation check: E1-proxy updates are slower than E2-proxy updates;
- no direct commitment check: representation outputs cannot bypass E3;
- attribution readiness check: outputs contain enough trace context for reafference comparison.
- uncertainty provenance check: every uncertainty value must declare estimator type (
dispersion/ensemble/head); - signed-PE boundary check: adapter does not emit control-plane valence labels as if they were representation-native authority labels.
- proxy provenance check: every active control proxy has
proxy_bankdeclaration fields. - confidence/residual separability check: confidence channel is not a direct alias of residual magnitude.
- ablation utility check: at least one declared proxy improves control/attribution behavior under matched seeds.
Failure Modes and Handling
-
FM-INT-001: Latent shortcut lock-in
Symptom: low training error with poor transfer under intervention shifts.
Handling: adversarial environment variants + counterfactual action sweeps. -
FM-INT-002: Representation adapter overreach into control
Symptom: adapter performs implicit action selection before E3.
Handling: strict interface check that adapter emits predictions only. -
FM-INT-003: Timescale collapse
Symptom: E1 and E2 update channels become indistinguishable.
Handling: enforce update-rate ratio thresholds and reject runs failing separation. -
FM-INT-004: Responsibility-blind predictions
Symptom: no usable attribution deltas for self-impact loops.
Handling: require action-conditioned traces and reafference comparison hooks in output pack.
Evidence Routing
Primary claim linkage:
MECH-057(control-completion requirement)Q-012(falsifiability of control necessity)
Evidence should be recorded via:
- literature:
evidence/literature/targeted_review_mech_057/** - experiments:
evidence/experiments/claim_evidence.v1.json
Acceptance Gate for Adoption
Adopt a JEPA-like representational adapter profile for E1/E2 interfaces only when all conditions hold:
- literature support for representation adequacy remains net-positive,
- experimental runs pass interface checks and stable-key metric checks,
- no unresolved evidence that the reference adapter bypasses REE commitment/control ownership,
- governance queue has explicit approval for adoption decision.
- adoption remains interface/reference scoped and does not make JEPA part of REE architecture.
Related Claims (IDs)
- IMPL-022
- IMPL-021
- IMPL-020
- MECH-057
- Q-012
- ARC-001
- ARC-002
- ARC-005
- ARC-015
Primary Source Anchors
The following source families were used to define the signal contract:
- I-JEPA paper (predictor over masked target representations): arXiv:2301.08243
- V-JEPA/V-JEPA2 methodology (mask-denoising in latent space, L1-style latent regression, action-conditioned autoregressive world model): arXiv:2506.09985
- JEPA uncertainty extension evidence (latent variables + variance/covariance regularization in non-deterministic futures): arXiv:2412.10925
- Reference implementation streams:
- I-JEPA training loop (
target_encoderlatent targets, predictor outputs,smooth_l1_loss): facebookresearch/ijepa/src/train.py - V-JEPA2 pretraining loop (latent prediction loss over masked tokens): facebookresearch/vjepa2/app/vjepa/train.py
- V-JEPA2 action-conditioned loop (
jlossteacher forcing +slossautoregressive rollout): facebookresearch/vjepa2/app/vjepa_droid/train.py
- I-JEPA training loop (