Pith Number

pith:QERLLBZP

pith:2026:QERLLBZPNL4Y5X7UQW2PP7ZH2F

not attested not anchored not stored refs resolved

VIP-COP: Context Optimization for Tabular Foundation Models

Leman Akoglu, Xueying Ding, Yilong Chen

VIP-COP estimates importance of training samples and features to build better contexts for tabular foundation models at test time.

arxiv:2605.12904 v1 · 2026-05-13 · cs.LG

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

VIP-COP consistently outperforms heuristic and optimized baselines across large-scale high-dimensional testbeds, including data augmentation and data-noise settings, establishing a new state of the art in test-time context refinement for TFMs.

C2weakest assumption

That the online KernelSHAP-based regression accurately identifies influential samples and features for prediction even when the model is treated as a black box and when data distributions differ from pretraining.

C3one line summary

VIP-COP is a black-box method that optimizes context for tabular foundation models by ranking and selecting high-value samples and features via online KernelSHAP regression, outperforming baselines on large high-dimensional data.

References

42 extracted · 42 resolved · 6 Pith anchors

[1] MIT press Cambridge, MA, USA, 2017 2017

[2] Unleashing the potential of prompt engineering for large language models.Patterns, 6(6) 2025

[3] Extending Context Window of Large Language Models via Positional Interpolation 2023 · arXiv:2306.15595

[4] Longlora: Efficient fine-tuning of long-context large language models 2023

[5] Cubuk, Barret Zoph, Dandelion Mané, Vijay Vasudevan, and Quoc V 2019

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T03:09:10.651450Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

8122b5872f6af98edff485b4f7ff27d17beffa549af2547eb2818c3e5e1ddd81

Aliases

arxiv: 2605.12904 · arxiv_version: 2605.12904v1 · doi: 10.48550/arxiv.2605.12904 · pith_short_12: QERLLBZPNL4Y · pith_short_16: QERLLBZPNL4Y5X7U · pith_short_8: QERLLBZP

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/QERLLBZPNL4Y5X7UQW2PP7ZH2F \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 8122b5872f6af98edff485b4f7ff27d17beffa549af2547eb2818c3e5e1ddd81

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "387e2715638bc7e6d2e8171ad89e188b7f7c15dd800279cc3b82e56c006a6f41",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-13T02:28:31Z",
    "title_canon_sha256": "78dd3fc48e3e262c806d041630e05175112cd989d21048f0e678b54a0376145f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12904",
    "kind": "arxiv",
    "version": 1
  }
}