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Paper Citation Record · LEDGER

ReAcTable: Enhancing ReAct for Table Question Answering

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.00815.

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

pith.paper-citation-record.v1
2310.00815 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:00:13.205035Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T21:40:40.893104Z

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 c0b95fd0-d7c7-4175-9670-db4e956c47d2 · inbound

Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models cites this paper.

Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models ReAcTable: Enhancing ReAct for Table Question Answering

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-11T19:00:13.205035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:00:13.205035Z digest=sha256:df74994463064c1e7dff676f85ca6ccf8e26a14eccd1bacca9d38ae4dbe2c61d

Observation c1b9fe4b-af69-4d3f-b7e0-e320c72546be · inbound

LLM Inference Enhanced by External Knowledge: A Survey cites this paper.

LLM Inference Enhanced by External Knowledge: A Survey ReAcTable: Enhancing ReAct for Table Question Answering

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:22.944325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:22.944325Z digest=sha256:def73ca7fea3176212da369b9bab19cae7522deb7d79d269a3d310d91e2f1e98

Observation d877f895-40ff-47ca-8d5e-236e0943009a · inbound

Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Models cites this paper.

Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Models ReAcTable: Enhancing ReAct for Table Question Answering

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T06:03:47.645265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:03:47.645265Z digest=sha256:dd92ede5be9e87b9bb749a7dd0e921fada58da6d3c4e26f7a5a3acc716082819

Observation 5c3e16a0-1208-4a1c-bb18-a4e185bf1e06 · inbound

What to Keep and What to Drop: Adaptive Table Filtering Framework cites this paper.

What to Keep and What to Drop: Adaptive Table Filtering Framework ReAcTable: Enhancing ReAct for Table Question Answering

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T21:47:41.852104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:41.852104Z digest=sha256:21105d6fe1a15a986ce48c93e40d51a6f565acb3ea12667888c480c6b742b6c8

Observation 2b364b45-bbe9-46a8-9432-7418941f7114 · inbound

ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation cites this paper.

ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation ReAcTable: Enhancing ReAct for Table Question Answering

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-19T04:42:04.830442Z

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=2026-05-19T04:37:33.942379Z digest=sha256:e065e3d4e4d2e6c722de31a945d59af69dd356e49912ea12ccb32fcca26d19a3

Observation 43632370-f14a-4c6f-8c06-f900a0f4cb95 · inbound

Utilizing Training Data to Improve LLM Reasoning for Tabular Understanding cites this paper.

Utilizing Training Data to Improve LLM Reasoning for Tabular Understanding ReAcTable: Enhancing ReAct for Table Question Answering

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:50.922518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:50.922518Z digest=sha256:e13f90c96271de99bf87e5d8ac446742a36d8b5bc8f7a9bec631ecd5fa2296cc

Observation 40176e4b-1044-4465-822a-d8be447166d1 · inbound

When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables cites this paper.

When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables ReAcTable: Enhancing ReAct for Table Question Answering

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-21T21:40:40.895492Z

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=arxiv_source observed=2026-05-21T21:38:09.388808Z digest=sha256:d7bf27551bd289d29276c08fbc6eb8a64951f13695173d52a9936370cb0858cb