Paper Citation Record · LEDGER

Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2311.05884.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2311.05884 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:59:54.001196Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T16:54:59.135304Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3c2147c6-4f62-4cef-a3aa-c0db89714401 · inbound

Improving feature interactions at Pinterest under industry constraints cites this paper.

Improving feature interactions at Pinterest under industry constraints Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T23:59:54.001196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0fee91a-e9b3-43ea-be34-5dfb00e1f6ef · inbound

RankMixer: Scaling Up Ranking Models in Industrial Recommenders cites this paper.

RankMixer: Scaling Up Ranking Models in Industrial Recommenders Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T15:35:48.349006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95fb2a6f-44d4-4d4b-ab52-e0f3fd604928 · inbound

From Scaling to Structured Expressivity: Rethinking Transformers for CTR Prediction cites this paper.

From Scaling to Structured Expressivity: Rethinking Transformers for CTR Prediction Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T22:08:54.962723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce41e478-714a-4f5a-b436-b69824ddb0ee · inbound

UniScale: Synergistic Entire Space Data and Model Scaling for Search Ranking cites this paper.

UniScale: Synergistic Entire Space Data and Model Scaling for Search Ranking Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:55:26.127154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f7b968dd-9391-4039-948d-856e2455f494 · inbound

IAT: Instance-As-Token Compression for Historical User Sequence Modeling in Industrial Recommender Systems cites this paper.

IAT: Instance-As-Token Compression for Historical User Sequence Modeling in Industrial Recommender Systems Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:01:01.301285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f331e419-9fd1-4ca5-a36c-2b53837a7827 · inbound

TokenFormer: Unify the Multi-Field and Sequential Recommendation Worlds cites this paper.

TokenFormer: Unify the Multi-Field and Sequential Recommendation Worlds Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:50:25.125727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7182b9f8-9e41-4da2-bf82-e453b64a4274 · inbound

RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems cites this paper.

RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:56:04.761352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 27943f23-ea4f-4b7e-817b-d423afcfe84b · inbound

RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems cites this paper.

RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:17:29.434971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2c930dc5-6381-47fc-a95e-0e74ca6aec39 · inbound

LoopCTR: Unlocking the Loop Scaling Power for Click-Through Rate Prediction cites this paper.

LoopCTR: Unlocking the Loop Scaling Power for Click-Through Rate Prediction Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:26:04.224776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 39ffe000-5d56-41dd-bba7-9948530c4013 · inbound

FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation cites this paper.

FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-22T08:21:16.735678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 867e3bdf-a028-4911-bd6c-009fd534120e · inbound

FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation cites this paper.

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-30T16:54:59.137882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d2b380ab-7400-4901-bb44-a492f3c351d6 · inbound

TMallGS: Scaling Unified Feature and Sequence Modeling for Generative E-commerce Search cites this paper.

TMallGS: Scaling Unified Feature and Sequence Modeling for Generative E-commerce Search Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T05:22:03.924701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4637f6f6-aadc-4cce-b7b9-5a8974239095 · inbound

WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture cites this paper.

WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T19:18:42.423542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ad71112-ff63-4f0b-abd4-68f2136e39ac · inbound

WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture cites this paper.

WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T04:17:56.594424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b907e643-ac41-41fa-b9b8-d951f41abce3 · inbound

UniRank: Benchmarking Ranking Models for Unified Sequential Modeling and Feature Interaction cites this paper.

UniRank: Benchmarking Ranking Models for Unified Sequential Modeling and Feature Interaction Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T11:07:55.942562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf90326d-fd8d-4d6c-b78f-32efa47d2124 · inbound

LO-FAR: A Cost-Aware Local Filter for Sparse Feature Ranking in Industrial Ad Recommendation cites this paper.

LO-FAR: A Cost-Aware Local Filter for Sparse Feature Ranking in Industrial Ad Recommendation Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T09:09:36.168554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50f6916b-a937-48a1-8bee-203d867aaae7 · inbound

SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation cites this paper.

SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-31T23:20:19.268498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac60bb36-fc01-44a4-ba1e-b3a171e124fa · inbound

SpecFormer: Mitigating Embedding and Attention Collapse via Spectral-Aware Transformer for Recommendation cites this paper.

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T04:02:20.028664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b337c37-1e4c-4ea3-81bf-7f6b92f0c334 · inbound

TransX: Scaling Transformer-based Recommendation via Behavioral and Serving Stream Crossings cites this paper.

TransX: Scaling Transformer-based Recommendation via Behavioral and Serving Stream Crossings Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T16:52:53.224823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.