Pith. sign in

Paper Citation Record · LEDGER

Agentic LLMs for Question Answering over Tabular Data

As of 21 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2509.09234.

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

pith.paper-citation-record.v1
2509.09234 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:30:45.155462Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 80e155f8-004d-43e6-b84d-29e733e7cfbb · outbound

This paper cites online" 'onlinestring :=.

Agentic LLMs for Question Answering over Tabular Data online" 'onlinestring :=

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:43.512115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:43.512115Z digest=sha256:3dfffb75d9b5eddcd02ae29cb8fbfac8afa3ccdbf27e4d3f806ca399573cc53d

Observation ef5436a3-a9f3-474d-97d9-d8936a45529a · outbound

This paper cites write newline.

Agentic LLMs for Question Answering over Tabular Data write newline

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:43.591340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:43.591340Z digest=sha256:34d5890a5e29aba3f5958369475aed65fa1a451f791ef443eab28dbfaada4d61

Observation bfcbd212-6fbb-46da-869b-e4c3c33d0245 · outbound

This paper cites an unresolved cited work.

Agentic LLMs for Question Answering over Tabular Data Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:43.667270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:43.667270Z digest=sha256:1be37d5a8bdcc12047fc6e4c04b2fba3af2657a7ea9b676ad83966c689405f9e

Observation 44a43f0d-6c3c-4c6d-b3e8-399113d2b810 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

Agentic LLMs for Question Answering over Tabular Data DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:43.775377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:43.775377Z digest=sha256:42781b426a27107df5637e1a1d117c8f20187be521fac3add49bc2f0f888225f

Observation 2cec3039-297b-4183-b484-8ea270eb1f59 · outbound

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

Agentic LLMs for Question Answering over Tabular Data Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:43.846224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:43.846224Z digest=sha256:25e6e12d5f7873d2185c1a0385ad56051443c28b72095bbc18a62b968cf158b6

Observation f19e185a-109f-46a6-8418-e068dfb6f070 · outbound

This paper cites an unresolved cited work.

Agentic LLMs for Question Answering over Tabular Data Unresolved cited work

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:43.928283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:43.928283Z digest=sha256:3c850adcbb300d82d6404318cff3dad3aabe452e1cb456f4a5c24f8585119031

Observation 6f283a0a-56d6-4970-8bca-cc2af3fc3024 · outbound

This paper cites an unresolved cited work.

Agentic LLMs for Question Answering over Tabular Data Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.011480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.011480Z digest=sha256:8d68361c53d53ed25b47486936819fb398eff6c0ce38d424180257b9db034043

Observation b05058be-e0f4-4bfe-8351-158240ff8b38 · outbound

This paper cites an unresolved cited work.

Agentic LLMs for Question Answering over Tabular Data Unresolved cited work

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.078940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.078940Z digest=sha256:d0a73db50a016c4c4180468fbc0bc560d23da589b9cc04961137a1393ebf1b3a

Observation 276ef2ab-9c99-465d-bc89-3430bf1af58b · outbound

This paper cites an unresolved cited work.

Agentic LLMs for Question Answering over Tabular Data Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.152620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.152620Z digest=sha256:3a2e7569df726c6b67aff558ebe0d013f1831447405296d95dc2a4cc63113b49

Observation 025680ca-7e43-44b1-8436-cfb9423eb82e · outbound

This paper cites A Survey on Table Question Answering: Recent Advances.

Agentic LLMs for Question Answering over Tabular Data A Survey on Table Question Answering: Recent Advances

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.195580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.195580Z digest=sha256:f9d74706bba3814ffc5991b4f019a4c94fb9ee3ceb260abadeca1809107902ca

Observation a7fc884b-5ca6-4565-b8de-ccdfbbb4fa3a · outbound

This paper cites an unresolved cited work.

Agentic LLMs for Question Answering over Tabular Data Unresolved cited work

Reference 11

Resolution
verified exact
doi, observed 2026-08-04T19:34:25.613802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-04T19:30:44.285862Z digest=sha256:14eab4c96146637c465b7f06541af5d34af632bb231545772e683c3b7dae5749

Observation 9b69591d-a13d-419e-a95e-2655ca4e2cc6 · outbound

This paper cites Divide and Prompt: Chain of Thought Prompting for Text-to-SQL.

Agentic LLMs for Question Answering over Tabular Data Divide and Prompt: Chain of Thought Prompting for Text-to-SQL

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.371146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.371146Z digest=sha256:fd26158aca88ed11c7a473014c40e0562a2aff98de3110d6a97b2aa71801bc8f

Observation 00594952-079c-47b1-8d98-afdffa7dad5a · outbound

This paper cites From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems.

Agentic LLMs for Question Answering over Tabular Data From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.445676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.445676Z digest=sha256:97a9ee272fc875cef1008243af5182f8488272d344db4a6a80100ec641478eb9

Observation 27618cd8-1a25-4d2d-9c2e-6da9bc1e99bc · outbound

This paper cites an unresolved cited work.

Agentic LLMs for Question Answering over Tabular Data Unresolved cited work

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.520851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.520851Z digest=sha256:610e8d4ec91d8a57c90ba2de8d89bef8c22a50e036a3ba6808adbd5e8a3ef8e9

Observation 052fb10a-494a-4b87-9af6-9642a5d32b44 · outbound

This paper cites End-to-End Table Question Answering via Retrieval-Augmented Generation.

Agentic LLMs for Question Answering over Tabular Data End-to-End Table Question Answering via Retrieval-Augmented Generation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.623315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.623315Z digest=sha256:25391fac27b0235ba9a87c0374b2e7ff13281c3f07ba650191305438647300d3

Observation 631450c5-5596-453d-9e96-7e760be26e87 · outbound

This paper cites Compositional Semantic Parsing on Semi-Structured Tables.

Agentic LLMs for Question Answering over Tabular Data Compositional Semantic Parsing on Semi-Structured Tables

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.700779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.700779Z digest=sha256:af255e628bbd8d76576a677d8d2661adbb3c7385c7dea073fb8908ce62d01778

Observation e7ba0a9e-6f2d-4c4d-8f37-5f258d600510 · outbound

This paper cites Are Small Language Models Ready to Compete with Large Language Models for Practical Applications?.

Agentic LLMs for Question Answering over Tabular Data Are Small Language Models Ready to Compete with Large Language Models for Practical Applications?

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.786694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.786694Z digest=sha256:443c2e15204235af769a81e60859a459920e54b9774c9acb089a4688ad07bf9d

Observation 55cea9d2-afca-4d8b-b977-4526f2bf46e7 · outbound

This paper cites A survey on advances in retrieval-augmented generation over tabular data and table qa.

Agentic LLMs for Question Answering over Tabular Data A survey on advances in retrieval-augmented generation over tabular data and table qa

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:44.907599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:44.907599Z digest=sha256:350dc56ee1a358397bacbbc48088c358cdde9386916aa6c843924da2de754d8b

Observation db89f05e-f524-4ca2-a97a-a9c480e5382d · outbound

This paper cites Tool-Assisted Agent on SQL Inspection and Refinement in Real-World Scenarios.

Agentic LLMs for Question Answering over Tabular Data Tool-Assisted Agent on SQL Inspection and Refinement in Real-World Scenarios

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:45.015054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:45.015054Z digest=sha256:ddb0461e6f3c7325ed64ab62e357223c9f2a377f809d11b9b646b47105dee6d4

Observation 4d512271-410a-469b-8ff1-72c469334c9c · outbound

This paper cites Cooperative SQL Generation for Segmented Databases By Using Multi-functional LLM Agents.

Agentic LLMs for Question Answering over Tabular Data Cooperative SQL Generation for Segmented Databases By Using Multi-functional LLM Agents

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:45.111981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:45.111981Z digest=sha256:f90e2a0e8bee5460a2b800db0c119a46eed286a958b9f440f84eb4e30221cebc

Observation 11b89ed0-da4f-4c60-a7bf-07483a4e609f · outbound

This paper cites Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task.

Agentic LLMs for Question Answering over Tabular Data Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-04T19:30:45.155462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:30:45.155462Z digest=sha256:7d447e9f15472e555a9387ff51cdb4dda02a8693daf77612cfc8d9af3f0f5d6a

Pith citing papers

No inbound Pith citation observations are available.