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Paper Citation Record · LEDGER

Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.14987.

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

pith.paper-citation-record.v1
2305.14987 v2

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 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:42:10.897402Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:55:43.403603Z

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 9f38e36f-b1e9-4d08-aa7d-af0e8b1a1b15 · inbound

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models cites this paper.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T13:42:10.897402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.897402Z digest=sha256:fb25cd43714dc80ea8b192d28cc7cc4e481411054f5a2d38c63cf4b5167499c7

Observation f18ccc3d-8134-465c-bce5-55550416341c · inbound

From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go cites this paper.

From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T20:46:35.888082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:46:35.888082Z digest=sha256:6711686f19e8305e8073d20e61726c41e0171e34406a1682674c4923d8920eae

Observation ff295801-40ee-41c8-a83c-82de71217701 · inbound

MDSF: Context-Aware Multi-Dimensional Data Storytelling Framework based on Large language Model cites this paper.

MDSF: Context-Aware Multi-Dimensional Data Storytelling Framework based on Large language Model Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T22:39:58.792370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:39:58.792370Z digest=sha256:517262ec715553c789d058658831c71fd3824223656140a9f75ea30702e24d7a

Observation 709971f4-7b05-433e-ba00-6a6a01ba3bb9 · inbound

A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges cites this paper.

A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios

Reference 268

Resolution
unresolved
no resolver link, observed 2026-08-10T22:17:23.970990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:17:23.970990Z digest=sha256:0c04302ba1696e782c18a9c437ba4d5be58368cda7f5ae71fa84023a1f4adbef

Observation ebc1f010-6d88-42ac-bb52-b72adb2e66a7 · inbound

Towards Efficient and Effective Alignment of Large Language Models cites this paper.

Towards Efficient and Effective Alignment of Large Language Models Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios

Reference 210

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:55:43.411707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T04:55:43.192292Z digest=sha256:16b7c5aa670ef5af61063e8a313d87de5264f19f64476e2b7714db43c5a02cd6