Paper Citation Record · LEDGER

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark

As of 6 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2508.21354.

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

pith.paper-citation-record.v1
2508.21354 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:24:24.931453Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:13:40.751517Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T11:13:44.946863Z

Reference resolution

25 of 25 outbound references displayed

verified exact4
verified fuzzy6
unresolved13
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cd24d7a3-d9bd-47c5-a2a5-2d5fe33d308c · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:22.828300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ffbc0a2-0e72-47ba-bb8b-f99f0203fbcf · outbound

This paper cites Revisiting Word Embeddings in the LLM Era.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Revisiting Word Embeddings in the LLM Era

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:24:26.533314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 296096be-3a16-4b79-840c-d3833d029893 · outbound

This paper cites Cross-domain recom- mendation via cluster-level latent factor model.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Cross-domain recom- mendation via cluster-level latent factor model

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:24:27.565748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 432d37dd-ca8b-43d2-a880-e5b918dbd239 · outbound

This paper cites DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:23.416343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0fe05b8-c40f-4c3b-a1e0-261ca3f49549 · outbound

This paper cites Beyond Utility: Evaluating LLM as Recommender.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Beyond Utility: Evaluating LLM as Recommender

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:24:26.199987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 270f586d-2c70-4437-8379-e1536549d8de · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark LLaVA-OneVision: Easy Visual Task Transfer

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:23.656589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 454176b1-a7b8-4305-8ce7-604688e57b73 · outbound

This paper cites Language model evolutionary algorithms for recommender systems: Benchmarks and algorithm comparisons.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Language model evolutionary algorithms for recommender systems: Benchmarks and algorithm comparisons

Reference 11

Resolution: verified exact; raw_fallback, observed 2026-08-05T14:24:25.989145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2a9a03a3-f8ef-43f0-a594-fd31154bfae9 · outbound

This paper cites Learning Multi-Aspect Item Palette: A Semantic Tokenization Framework for Generative Recommendation.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Learning Multi-Aspect Item Palette: A Semantic Tokenization Framework for Generative Recommendation

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T14:24:25.704029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9e86968c-dee9-44df-a41b-9302cd6da27a · outbound

This paper cites Hoang Ngo and Dat Quoc Nguyen.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Hoang Ngo and Dat Quoc Nguyen

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:24:27.276982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7f9fe0d4-2ca8-44b0-8a74-9eaad73f86f8 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:23.949796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7062efb2-2a0d-41e8-9090-ee26b38ceb14 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark LLaMA: Open and Efficient Foundation Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:24.033316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43b18f6b-b4c0-4bd1-bf96-58f60edd7fd0 · outbound

This paper cites Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:24.104785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c220245a-184c-45d5-8b9e-9a3026985f8d · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:24.212069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f450759c-f499-4202-95d5-92069a023be1 · outbound

This paper cites A survey on large language models for recommendation.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark A survey on large language models for recommendation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:24:27.054082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ce3d5b05-4cbc-44e8-bf90-2cef063a2978 · outbound

This paper cites Qwen2 Technical Report.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Qwen2 Technical Report

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:24.498733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d44194c-7aa7-4aea-87a4-2607d83c1327 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark OPT: Open Pre-trained Transformer Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:24.573508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d9488c5-7796-4d58-b948-62ae9841d120 · outbound

This paper cites Language models as recommender systems: Evalua- tions and limitations.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Language models as recommender systems: Evalua- tions and limitations

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:24:26.915899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4ccaed1e-689a-4b7d-a60e-30461996e99f · outbound

This paper cites 2024.3392335.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark 2024.3392335

Reference 23

Resolution: malformed identifier; no resolver link, observed 2026-08-05T14:24:24.745262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8439bf3-dacb-4a59-ac3b-b03c0dad99a3 · outbound

This paper cites C.2 Additional Evaluation Metrics In the main text, we report only the AUC metric due to the space constraints.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark C.2 Additional Evaluation Metrics In the main text, we report only the AUC metric due to the space constraints

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:24:26.757690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 68d16a66-1a19-4ee6-b588-dac23a91fb01 · outbound

This paper cites The Llama 3 Herd of Models.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark The Llama 3 Herd of Models

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:23.081553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97fffeb3-4241-456c-ab68-8a4ad6d3a7f6 · outbound

This paper cites TF-DCon: Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark TF-DCon: Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation

Reference 2019

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:24:25.361532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 354ee563-3200-4764-b97d-13d036a6ca52 · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:23.352696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2974f55-6519-4442-9380-10258ce9dce8 · outbound

This paper cites Mistral 7B.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Mistral 7B

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:23.504111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 541190a3-df68-4da1-bc0b-d6ba231267ea · outbound

This paper cites Differential private knowledge transfer for privacy-preserving cross-domain recommendation.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Differential private knowledge transfer for privacy-preserving cross-domain recommendation

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:24:27.760426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4e87e01f-a252-41e5-98a9-84c7adacf045 · outbound

This paper cites Cross-Domain Recommendation: Challenges, Progress, and Prospects.

Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark Cross-Domain Recommendation: Challenges, Progress, and Prospects

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T14:24:24.858493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 7917368b-6bf0-4154-9537-afc4211d5087 · inbound

RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation cites this paper.

RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:13:45.012281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.