dial-workshop-data / nodes /vavvi2-1 /protocol /dial_protocol.json
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{
"schema_version": 1,
"study_id": "dial_lexical_differentiation_v1",
"title": "Differentiate Before You Integrate? When Embedding Factorization Becomes an Inductive Bias in Data-Limited Language Acquisition",
"frozen_at_utc": "2026-07-19T21:14:38Z",
"fixed_compute_deadline_utc": "2026-07-20T09:14:38Z",
"status": "prospective_before_any_dial_training_or_outcome_access",
"primary_question": "Does temporarily protecting complementary relational signals at lexical access reduce cross-talk and change acquisition before shared Transformer integration?",
"claim_boundary": {
"positive": "A temporary input-level relational scaffold changes the acquisition trajectory relative to an information-matched overlapping-support control.",
"excluded": [
"persistent cognitive modules",
"human neural equivalence",
"grounded conceptual representations",
"universal architectural optimality",
"leaderboard superiority",
"Poincare geometry"
]
},
"conditions": {
"aligned": "Real H/O/A relations in three disjoint orthogonal rank-128 input supports.",
"shared": "The exact same real H/O/A relations in three fixed dense overlapping rank-128 supports; each block is orthonormal and the concatenated condition number must be below 3.",
"shuffled": "Aligned supports with one identity permutation shared across all three relation views and restricted within frozen matching strata."
},
"operational_relations": {
"H": "Hierarchical-distributional Brown radial-angular targets.",
"O": "Order-sensitive directional relative-position PPMI at offsets -3,-2,-1,+1,+2,+3.",
"A": "Associative-distributional symmetric PPMI."
},
"architecture": {
"backbone": "dense PRISM GPT-BERT",
"hidden_size": 384,
"rank_allocation": [128, 128, 128],
"embedding_tables": 1,
"transformer_streams": 1,
"shared_transformer_from_layer": 1,
"input_output_embeddings_tied": false,
"final_factor_readout": false,
"parser": false,
"attention_masks_from_priors": false,
"block_specific_normalization": false
},
"scaffold": {
"loss": "L_LM + lambda(t) * sum_k alpha_k L_k",
"lambda_schedule": "lambda0 * max(0, 1 - words_seen / 10000000)",
"withdrawal_words": 10000000,
"calibration_minibatch": 0,
"alpha_rule": "equalize initial H/O/A gradient norms on the input embedding table",
"lambda0_rule": "aggregate auxiliary gradient norm divided by LM gradient norm equals 0.25",
"outcome_tuning": false,
"orthogonality_penalty": false,
"cross_covariance_role": "diagnostic_only",
"structured_initialization": "0.75 fixed relational solution plus 0.25 paired isotropic initialization, renormalized to the registered initializer RMS"
},
"design": {
"paired_seeds": [0, 1, 2, 3, 4, 5],
"conditions_per_seed": 3,
"fresh_models": 18,
"terminal_exposure_words": 40000000,
"learning_rate_schedule_words": 100000000,
"checkpoints_words": [1000000, 2000000, 3000000, 4000000, 5000000, 6000000, 7000000, 8000000, 9000000, 10000000, 20000000, 30000000, 40000000],
"same_within_pair": [
"non-embedding initialization",
"document and batch order",
"dropout stream",
"edge batches",
"optimizer",
"gradient clipping",
"corpus",
"tokenizer",
"relation arrays",
"auxiliary schedule"
],
"intended_difference": "support overlap or the frozen shared identity permutation only"
},
"primary_endpoint": {
"battery": ["BLiMP", "COMPS", "EWoK", "Entity Tracking"],
"model_outputs": "native LM probabilities without fine-tuning or probes",
"trajectory": "equal-weight composite AUC over log exposure from 1M through terminal exposure",
"contrast": "aligned minus shared",
"falsification_gate": "aligned greater than shuffled",
"normalization": "independent frozen baseline only; otherwise equal-accuracy mean"
},
"validity_gates": {
"lm_loss_noninferiority_nats_per_token": 0.02,
"minimum_shuffle_direction": "aligned greater than shuffled",
"random_basis_controls": 32,
"random_basis_matching": ["rank", "energy"],
"maximum_failed_seeds_per_condition": 1,
"systematic_throughput_or_clipping_difference_allowed": false
},
"mechanism": {
"checkpoint_ages_words": [1000000, 10000000, 40000000],
"intervention": "input-block donor swaps matched by frequency, subword length, norm, coverage and degree",
"controls": "32 Haar-random equal-rank equal-energy bases",
"joint_interventions": "all 2^3 H/O/A swaps",
"interaction": "non-additive HxOxA contrast",
"gradient_audit_minibatches": 64,
"gradient_audit": "LM versus H/O/A cosine and conflict rates",
"imposed_not_result": "between-support orthogonality in aligned"
},
"cognitive_bridge": {
"primary": "AoA prediction with frequency, length, contextual diversity and lexical class controls, including within-frequency-bin effects",
"secondary": "cross-validated log1p self-paced reading time, grouped by the 205 sentences, with frequency, length, position, spillover and paired shared-condition surprisal controls",
"exploratory": "ERP only; no post-hoc mapping from subspaces to components",
"human_causality_claimed": false
},
"statistics": {
"unit": "paired training seed",
"primary_test": "two-sided exact paired sign-flip",
"minimum_attainable_two_sided_p": 0.03125,
"report": ["every seed", "paired effect", "confidence interval"],
"no_checkpoint_pseudoreplication": true
},
"compute_fallback": {
"decision_input": "preflight throughput only, before outcome access",
"if_predicted_wall_time_to_40m_exceeds_hours": 8.5,
"fallback_terminal_exposure_words": 30000000,
"node_failure": "retain complete balanced pairs only, first five then first four seeds",
"forbidden": "asymmetric condition truncation or metric-driven adaptation"
},
"priority_order": [
"primary acquisition composite",
"AoA",
"input swaps",
"gradient conflict",
"reading time",
"full zero-shot for one preregistered model",
"SuperGLUE",
"ERP",
"embedding visualization"
],
"artifact_policy": {
"model_checkpoints": "all registered ages plus 40M main and recovery on Hugging Face",
"priors_tokenizer_corpus": "pinned Hugging Face revisions",
"study_archive": "data and machine-readable provenance only",
"adaptive_result_access_before_all_lineages_sealed": false
},
"retrospective_context_only": [
"FACTORIZED tournament",
"FACTORIZED mechanism study",
"factorized resource substitution study",
"STRUCTURED-DS tournament"
]
}