{
  "name": "recICL",
  "model_type": "icl-recommender",
  "architecture": "RecPFN",
  "architecture_source": "https://github.com/SAP-samples/tabular-ai-recpfn (upstream commit 1af320c, Apache-2.0)",
  "paper": "arXiv:2608.19735 (SIGIR '26), doi:10.1145/3805712.3809696",
  "embedding_dim": 1536,
  "n_parameters": 169918464,
  "dtype": "float32",
  "model_config": {
    "n_layers": 4,
    "n_heads": 8,
    "dropout": 0.2,
    "icl_module_type": "alternating",
    "positional_embedding_scheme": "hard-alibi",
    "max_sequence_len": 15,
    "train_with_icl": true,
    "num_icl_examples": 8,
    "icl_k": 2,
    "weighted_icl_sampling": true,
    "weighted_decay_rate": 1.0,
    "normalize_embs": true,
    "llm": "qwen1b",
    "baseline_config": "balanced"
  },
  "inference": {
    "history_items_used": 14,
    "context_sequence_max_len": 15,
    "num_context_sequences": 8,
    "context_retrieval": "SAP InvertedIndexMatcher: pool sequences cut into windows of 15 (step 7); candidates share one of the query's last 2 items; top 8 by recency-weighted Jaccard (decay 1.0)",
    "score": "dot product of the output at the last history position with each L2-normalised item embedding"
  },
  "item_embeddings": {
    "model_id": "Alibaba-NLP/gte-Qwen2-1.5B-instruct",
    "revision": "a9af15a6372d7d6b25e9fb07c2ccb9e1fe645644",
    "dim": 1536,
    "trust_remote_code": true,
    "compute_dtype": "bf16",
    "max_seq_length": 512,
    "prompt": null,
    "pooling": "last token (<|endoftext|> appended by the remote-code tokenizer), right padding",
    "normalization": "L2 in fp32",
    "amazon_item_text_format": "Title: {title}; Brand: {brand}; Categories: {c1, c2, ...}"
  },
  "training": {
    "code": "SAP-samples/tabular-ai-recpfn src/ at 1af320c + infrastructure patches (resume, logging, NaN diagnostics; opt-in fixes all OFF) - training math as released",
    "config": {
      "train_with_icl": true,
      "num_icl_examples": 128,
      "train_with_synthetic_data": true,
      "n_layers": 4,
      "batch_size": 16,
      "reg_lambda": 0.0001,
      "warmup_epochs": 6,
      "baseline_config": "balanced",
      "learning_rate": 0.0001,
      "early_stopping_patience": 20,
      "positional_embedding_scheme": "hard-alibi",
      "optimizer": "adamw",
      "llm": "qwen1b",
      "max_sequence_len": 15,
      "num_epochs": 120,
      "use_cached_embeddings": true,
      "num_gradient_accumulation_steps": 2,
      "early_stopping_metric": "hr@10",
      "loss": "sce",
      "train_epoch_size": 500,
      "val_epoch_size": 200,
      "num_sdg_items": 1000,
      "normalize_embs": true,
      "n_heads": 8,
      "dropout": 0.2,
      "icl_module_type": "alternating",
      "val_k": 10
    },
    "training_seed": 0,
    "optimizer": "AdamW (torch defaults besides lr), linear warmup for warmup_epochs, then cosine annealing to 0.01*lr",
    "data": "synthetic sequences only (no real user data); each batch = one synthetic environment of 1000 items whose embeddings are sampled from the embedding store below",
    "embedding_store": {
      "rows": 800000,
      "composition": {
        "fiqa": 64248,
        "quora": 200000,
        "fever": 200000,
        "msmarco": 335752
      },
      "sources": "BEIR (FiQA-2018, Quora, FEVER, MS MARCO), sampled with seed 0",
      "encoder": "same as item_embeddings",
      "sha256": "fb9374462837c1b41188d15d50c55faf04096373f918ea31be57ddcdd6a29620"
    },
    "stages": {
      "stage1": {
        "synthetic_prior": "random graph",
        "sdg_params": {
          "transition_matrix_prior": [
            "random_graph"
          ],
          "popularity_bias": [
            0.0,
            0.1,
            0.2,
            0.3,
            0.5
          ],
          "window_size": [
            1,
            2,
            3
          ],
          "decay_coeff": [
            0.5,
            0.8
          ],
          "repeated_items": [
            true
          ]
        },
        "init": "random (seed 0)",
        "epochs_run": 120,
        "best_epoch": 101,
        "early_stopped": false,
        "best_synthetic_ratio_hr@10": 7.974883964010977,
        "gpu": [
          "NVIDIA H200"
        ],
        "wall_hours": 2.573,
        "first_epoch_end": "2026-09-29T07:33:10Z",
        "finished": "2026-09-29T10:05:54Z"
      },
      "stage2": {
        "synthetic_prior": "random graph + latent factor",
        "sdg_params": {
          "transition_matrix_prior": [
            "random_graph",
            "latent_factor"
          ],
          "num_latent_concepts": [
            20,
            40,
            60
          ],
          "mean_num_concepts_per_item": [
            2,
            3,
            5
          ],
          "mean_num_concepts_per_user": [
            2,
            3,
            5
          ],
          "popularity_bias": [
            0.0,
            0.1,
            0.2
          ],
          "window_size": [
            1,
            2,
            3
          ],
          "decay_coeff": [
            0.5,
            0.8
          ],
          "logit_scale": [
            9.0,
            12.0
          ],
          "concept_matrix_diagonal_deviation_rate": [
            0.0,
            0.1,
            0.3
          ],
          "repeated_items": [
            true
          ],
          "mean_num_related_items": [
            1,
            3,
            5,
            7
          ],
          "repeated_item_probability": [
            0.1,
            0.2,
            0.3
          ]
        },
        "init": "stage-1 best checkpoint (epoch 101)",
        "epochs_run": 47,
        "best_epoch": 27,
        "early_stopped": true,
        "best_synthetic_ratio_hr@10": 3.9308144874246915,
        "gpu": [
          "NVIDIA H100 80GB HBM3"
        ],
        "wall_hours": 1.099,
        "first_epoch_end": "2026-09-29T10:07:51Z",
        "finished": "2026-09-29T11:11:55Z"
      }
    },
    "early_stopping": "hr@10 ratio (model / EmbKNN-balanced) on synthetic validation batches, patience 20",
    "selection": {
      "note": "best of our 9 training runs by mean validation HR@10 over the 7 Amazon validation splits",
      "amazon7_val_hr@10": 0.13147873010138936,
      "amazon7_val_hr@10_rank": 1,
      "amazon7_val_mrr@10": 0.0884027748063644,
      "amazon7_val_mrr@10_rank": 2,
      "n_runs": 9
    }
  },
  "evaluation_protocol": {
    "split": "user-level 70/10/20, seed 42; at most 10,000 users sampled into the test split, then users with a single interaction dropped",
    "target": "each test user's last item; input = up to 14 preceding items",
    "context": "8 sequences from train-split users (retrieval as in 'inference')",
    "batch_size": 1,
    "ranking": "full item catalog, no candidate sampling, repeated items allowed",
    "metrics": [
      "HR@10",
      "MRR@10"
    ],
    "hardware": "NVIDIA L4, fp32, TF32 off"
  },
  "checkpoint": {
    "source": "release_k4_s0/stage2/model.pth",
    "source_sha256": "661fd3415a0b8f2d727898006e6314dcd273e15f59da3383668f7bc1a3997a3a",
    "safetensors_sha256": "02c4edc3a4944a9e7a0b6025217b3ea7af16e53c9483e85e9a573074a228a60c",
    "safetensors_bytes": 679680696,
    "n_tensors": 64,
    "src_fingerprint": "6c3ca6431e028e27"
  }
}