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Paper Citation Record · LEDGER

ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language Models

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2502.20196.

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

pith.paper-citation-record.v1
2502.20196 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T01:23:14.783519Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:58:32.771675Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 3a820b4e-c9c0-4ecb-9769-6ac2a71f54ee · inbound

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models cites this paper.

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language Models

Reference 78

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:40:41.781932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-12T08:40:40.910461Z digest=sha256:e5cae5988ff77f82c26fd18c82e4d5841237136bf0484000601558f62698691a

Observation 6f0e44b7-6fd7-424b-a31c-2bb890b4c3a8 · inbound

UserGPT Technical Report cites this paper.

UserGPT Technical Report ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language Models

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-12T03:11:18.738580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-12T03:10:51.555653Z digest=sha256:4f9ae5b95fd159d2dab83f03c19137bb98da0281c9d88ade7311aa2dc82f80f9

Observation f7b8474b-2c8c-41b2-abe0-022cf9af65a5 · inbound

OxyEcomBench: Benchmarking Multimodal Foundation Models across E-Commerce Ecosystems cites this paper.

OxyEcomBench: Benchmarking Multimodal Foundation Models across E-Commerce Ecosystems ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language Models

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-14T02:18:37.609576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-14T02:13:53.218695Z digest=sha256:785ca54ca054e759a27547f5646e92f7b52a17457c89b1b6fa99855d3fab4904

Observation 51a1d65d-1fae-48cb-a622-19a6b8fb4aef · inbound

One Polluted Page Is Enough: Evaluating Web Content Pollution in Generative Recommenders cites this paper.

One Polluted Page Is Enough: Evaluating Web Content Pollution in Generative Recommenders ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language Models

Reference 44

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T14:58:32.772923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-27T06:51:09.529094Z digest=sha256:a802674453607afb987515348e70ef424968a66a9f36e3125224909d643aab48

Observation 19097398-cd32-4dab-b5d8-ab1089625ed6 · inbound

Can LLM Agents Price Competitively? A Dynamic Multi-Attribute Auction Benchmark for Agentic Commerce cites this paper.

Can LLM Agents Price Competitively? A Dynamic Multi-Attribute Auction Benchmark for Agentic Commerce ChineseEcomQA: A Scalable E-commerce Concept Evaluation Benchmark for Large Language Models

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-04T01:23:14.783519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T01:23:14.783519Z digest=sha256:0d9e27e37df0539a926c56a35f4f9d1e57c86a7b3380892819db5186ac98422c