Pith. sign in

Paper Citation Record · LEDGER

Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2503.04783.

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

pith.paper-citation-record.v1
2503.04783 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 2026-08-15T06:32:42.880941+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:11:05.309517Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T06:25:57.937734Z

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 012911c5-e066-487b-912c-b909f6b4843a · inbound

Evaluation of LLMs for mathematical problem solving cites this paper.

Evaluation of LLMs for mathematical problem solving Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T12:11:05.309517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:11:05.309517Z digest=sha256:33a031c80a34d29a22533e2d3629ab3795ff965fdfdf8bf4c7d69099929aea1c

Observation 4307d9ec-f997-45e9-9ecf-40e9dd78260c · inbound

Cat and Mouse -- Can Fake Text Generation Outpace Detector Systems? cites this paper.

Cat and Mouse -- Can Fake Text Generation Outpace Detector Systems? Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T22:34:09.615392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:34:09.615392Z digest=sha256:743b852d9742fa9528ff14d9501ca556e225bb3836c8d2a15fdaa36e4c2e49ef

Observation 5dac94be-7f68-41ce-8079-9cd3edf598d8 · inbound

A Survey of the State-of-the-Art in Conversational Question Answering Systems cites this paper.

A Survey of the State-of-the-Art in Conversational Question Answering Systems Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-05T05:11:25.263932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:11:25.263932Z digest=sha256:21d883dc5b71334095c6772e3f3dd7866b5e41735e58f6d9cd96688fcb56d803

Observation a5951b65-cae5-4fe0-bd08-4a078b3eb216 · inbound

Syntax Is Easy, Semantics Is Hard: Evaluating LLMs for LTL Translation cites this paper.

Syntax Is Easy, Semantics Is Hard: Evaluating LLMs for LTL Translation Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:25:57.940438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T17:39:31.790847Z digest=sha256:3154514696eb4c60504f432ac696740c6799dbdf1b7fd8c904322de5bac083ce

Observation 4c414a03-4d08-4a76-84e2-6026bb3c196a · inbound

No Universal Courtesy: A Cross-Linguistic, Multi-Model Study of Politeness Effects on LLMs Using the PLUM Corpus cites this paper.

No Universal Courtesy: A Cross-Linguistic, Multi-Model Study of Politeness Effects on LLMs Using the PLUM Corpus Comparative Analysis Based on DeepSeek, ChatGPT, and Google Gemini: Features, Techniques, Performance, Future Prospects

Reference 41

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T08:48:01.603901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T08:45:56.996410Z digest=sha256:174f535e194f63aef8f92efb65713984d3ea792ffc261d6f23604e703ad23f5b