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Paper Citation Record · LEDGER

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges

As of 19 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 4 inbound Pith citation observations for arXiv:2508.00217.

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

pith.paper-citation-record.v1
2508.00217 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:20:37.496053Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:39:47.868302Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:59:57.575882Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7a66a182-0cba-40de-b590-739083f2280d · outbound

This paper cites Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T10:20:37.444377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:20:37.444377Z digest=sha256:80f59ae620f663f4a8aee99a7c92cb0b9866c609ddf09a804ad777a5b4b2ea27

Observation 71835dfb-2f17-4cf5-a232-da0ddc95fab5 · outbound

This paper cites ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T10:20:37.459444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:20:37.459444Z digest=sha256:e8f6d92e0dbb2ad2ef6148950a28a684ac9285413b2c70f64c45016d8c34968b

Observation 4ac334af-f4d9-4593-b7f2-094e3016bebb · outbound

This paper cites TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T10:20:37.620008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T10:20:37.469564Z digest=sha256:8197e20ca186ce177b721e66221f42684c46e8feac0019cd4383aeb60b3942a3

Observation 8a0b4738-54fe-4e94-b6b0-037775c0580c · outbound

This paper cites Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T10:20:37.485930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:20:37.485930Z digest=sha256:921473f1794286395dc34a0ca63c1ab9c366f284376e0502a3e8f4e4b038d242

Observation aa1e52a9-b110-4709-9449-e502ac7ebd25 · outbound

This paper cites Multimodal Table Understanding.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Multimodal Table Understanding

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T10:20:37.490875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:20:37.490875Z digest=sha256:5b5212a9c2bf4227f683f14148425132324a4ce12059acf55745c78737fba2e4

Observation a7578b51-1415-4c46-baab-e65eb3fb0636 · outbound

This paper cites Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-06T10:20:37.496053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:20:37.496053Z digest=sha256:4129a9410b0707827390be03a1b4cebb840769161d47d203e1d81a38e7b1065e

Observation ea4af853-c5a0-4cbe-bce5-51f770a23754 · outbound

This paper cites Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation

Reference 2019

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:20:37.598093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T10:20:37.475070Z digest=sha256:c2c42971689cd74fab93dde68e0bc608962e98075d3c2d7602376e908a1b3331

Observation 80dace86-70a3-451b-80ea-1d0f597831e2 · outbound

This paper cites Computer Speech and Language, 59:123–156.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Computer Speech and Language, 59:123–156

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:20:37.710002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T10:20:37.449387Z digest=sha256:320fab5ac83fa2cbef552660e2affa8ecd03d4201725f8c621c620b655072f9d

Observation d2b0d76c-c643-4a41-83c6-747fa66505a8 · outbound

This paper cites Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-06T10:20:37.480621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:20:37.480621Z digest=sha256:b18016bf282521a53c1b3679b7a63d269ce19f4f364c11586cd8242d5f9e068a

Observation d79fec80-8707-442a-8ef2-758ccc2bf7cc · outbound

This paper cites Open-WikiTable: Dataset for Open Domain Question Answering with Complex Reasoning over Table.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Open-WikiTable: Dataset for Open Domain Question Answering with Complex Reasoning over Table

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T10:20:37.464609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:20:37.464609Z digest=sha256:1c28b1a447b0913f2c51b09c7dc8b19e7c151c03309265e4827d2b870c0dcd73

Observation acee0a58-6f68-4292-a0bd-abefcc9bc119 · outbound

This paper cites Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T10:20:37.438899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:20:37.438899Z digest=sha256:3a4b5f19533f5bacf49a03be0e5d5e7df71c91d0ef07c2267a20d74a32d6ad44

Observation 3fc85907-f78e-4c08-8251-13f8d2e38311 · outbound

This paper cites Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey.

Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T10:20:37.454189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:20:37.454189Z digest=sha256:5e53be891b81173ed3a83eda814315454026eea33317c545230d8d3a4db0929d

Pith citing papers

Observation 13567b7e-643a-4ce4-bb41-616ad38b70b4 · inbound

Towards Agents That Know When They Don't Know: Uncertainty as a Control Signal for Structured Reasoning cites this paper.

Towards Agents That Know When They Don't Know: Uncertainty as a Control Signal for Structured Reasoning Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-05T11:39:47.868302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:39:47.868302Z digest=sha256:ea1c2ce0ce6ec30f82480be3124b8c7e7e9097c7db1112cf32cb70876a32d55f

Observation 711676af-4194-4a4e-b332-fb5af05e63a1 · inbound

LLM-Based Instance-Driven Heuristic Bias In the Context of a Biased Random Key Genetic Algorithm cites this paper.

LLM-Based Instance-Driven Heuristic Bias In the Context of a Biased Random Key Genetic Algorithm Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T05:31:06.676790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:31:06.676790Z digest=sha256:2460f5a794b3f31bb083c64eac0bc99fe5d8b82f78daddb7d76616b404ac985c

Observation 3946fa1f-df2b-4864-bdf0-9ee24ef90332 · inbound

Large language model-enabled automated data extraction for concrete materials informatics cites this paper.

Large language model-enabled automated data extraction for concrete materials informatics Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges

Reference 89

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:41:08.745787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-08T11:17:46.387553Z digest=sha256:0773ba39a6a40897585a50974cb96d5944e46a8aaf632caf90624b59ac163c3c

Observation fbbb50b3-77ca-4858-9b6b-22dab4f805d8 · inbound

Large language model-enabled automated data extraction for concrete materials informatics cites this paper.

Large language model-enabled automated data extraction for concrete materials informatics Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challenges

Reference 89

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:59:57.577654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-07-04T16:51:19.852113Z digest=sha256:bc9a19f2789a1a5ec310fa99153643f1f0ce49405abc37855db9c32223314c41