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Paper Citation Record · LEDGER

What to Keep and What to Drop: Adaptive Table Filtering Framework

As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2506.23463.

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

pith.paper-citation-record.v1
2506.23463 v3

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:47:41.945165Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

33 of 33 outbound references displayed

  • verified exact2
  • verified fuzzy14
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 41133cf5-a998-46af-a9dc-5c15f8926e05 · outbound

This paper cites A theory of learning from different domains.

What to Keep and What to Drop: Adaptive Table Filtering Framework A theory of learning from different domains

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:45.414434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:39.325490Z digest=sha256:76f0f3b4f191b855f3987e43687d466a9db77cc5cb0c571de23cebf4a3ade270

Observation 656d6d4b-cfe0-4730-82bc-14b22231903f · outbound

This paper cites TableRAG: Million-Token Table Understanding with Language Models.

What to Keep and What to Drop: Adaptive Table Filtering Framework TableRAG: Million-Token Table Understanding with Language Models

Reference 2

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unresolved
no resolver link, observed 2026-08-06T21:47:39.398888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:39.398888Z digest=sha256:2291753af50a5d4a4cedbb20837ae5ab4ee21e4cd09cdee4bf5e631db30d89f6

Observation dadb6d29-3762-4a4e-8fed-a1f5454536d9 · outbound

This paper cites Tabfact: A large-scale dataset for table-based fact verification.

What to Keep and What to Drop: Adaptive Table Filtering Framework Tabfact: A large-scale dataset for table-based fact verification

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:45.262479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:39.503619Z digest=sha256:6a240f0a2c564cf5c1ce2008ab65d25dceba3eac708aeef81036290c08ddd202

Observation 447befda-3aa2-4739-90ce-dd4fddfad51a · outbound

This paper cites Binder: Binding language models in symbolic languages.

What to Keep and What to Drop: Adaptive Table Filtering Framework Binder: Binding language models in symbolic languages

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:45.085824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:39.598304Z digest=sha256:0e6b55e29d839dcb29ad1cf6a1e50c889aa409601a6d6dda067773801b7ac4bc

Observation 7537a1f6-847d-45b4-9ffe-2bc6aa6569db · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

What to Keep and What to Drop: Adaptive Table Filtering Framework BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 5

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no resolver link, observed 2026-08-06T21:47:39.718567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:39.718567Z digest=sha256:10dfaa99e94573bc2be8c1341f26f75cecadf2c953758a4a72b3b87a3781adb6

Observation b36c6c50-6c87-42b1-b3f3-639133d677ab · outbound

This paper cites Mate: Multi-view attention for table transformers.

What to Keep and What to Drop: Adaptive Table Filtering Framework Mate: Multi-view attention for table transformers

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:44.876883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:39.793239Z digest=sha256:24f3fdda6d5e5a188f101d982f2b3e4a1aa8b3a17c02d1535c97d62e363453e0

Observation 72cc219d-957f-41f0-ae88-1547ea975bb1 · outbound

This paper cites Llm chain ensembles for scalable and accurate data annotation.

What to Keep and What to Drop: Adaptive Table Filtering Framework Llm chain ensembles for scalable and accurate data annotation

Reference 7

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no resolver link, observed 2026-08-06T21:47:39.882181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:39.882181Z digest=sha256:2011a511f3d0a5597a1464f02eebaa44300bad3b4c220f2fd6d3d981509e025b

Observation e01e0f4c-ed1e-4315-97a2-d644ffe07b87 · outbound

This paper cites Blendsql: A scalable dialect for unifying hybrid qa in relational algebra, 2024.

What to Keep and What to Drop: Adaptive Table Filtering Framework Blendsql: A scalable dialect for unifying hybrid qa in relational algebra, 2024

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:44.695294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:39.964324Z digest=sha256:abb4d0c2242714210a0e9cc39dc045f3e76f15384d8989c6bd91c8a4903fd3f1

Observation 10b25185-250c-43e4-bf72-57e0fefbaea2 · outbound

This paper cites Nonlinear 1-Bit Precoding for Massive MU-MIMO with Higher-Order Modulation.

What to Keep and What to Drop: Adaptive Table Filtering Framework Nonlinear 1-Bit Precoding for Massive MU-MIMO with Higher-Order Modulation

Reference 9

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T21:47:42.641521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.057294Z digest=sha256:ed4f699816d702c8903fc6d69e5216681f21791427db301c50a39e9631d73e16

Observation 71f489e6-271b-41dd-bcb7-d73bc1503d47 · outbound

This paper cites Tapas: Weakly supervised table parsing via pre-training.

What to Keep and What to Drop: Adaptive Table Filtering Framework Tapas: Weakly supervised table parsing via pre-training

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:44.518440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.171219Z digest=sha256:369e7024be1ddfa3cb17534daf542354ef3afe079575659762c68ff5f3bea1b4

Observation 893ea451-9990-4044-9ce4-f6b43f98f64d · outbound

This paper cites An Introduction to Statistical Learning.

What to Keep and What to Drop: Adaptive Table Filtering Framework An Introduction to Statistical Learning

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:44.305769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.243072Z digest=sha256:70132ada2606f83999f244515888b57823b9647aac82e16d9e290ff9e9920280

Observation f263909e-ded6-4e5c-af04-dcc0cf4e3e62 · outbound

This paper cites A statistical interpretation of term specificity and its application in retrieval.

What to Keep and What to Drop: Adaptive Table Filtering Framework A statistical interpretation of term specificity and its application in retrieval

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:44.055818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.323666Z digest=sha256:9e6bb8c2f22d2784d93bfb1c9f4817179ab120ce9e70ffd24633c0ee19b1b97a

Observation 7fa51d79-7ae3-4ce1-9dfe-bbb0a743e377 · outbound

This paper cites Ait-qa: Question answering dataset over complex tables in the airline industry, 2021.

What to Keep and What to Drop: Adaptive Table Filtering Framework Ait-qa: Question answering dataset over complex tables in the airline industry, 2021

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:43.797142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.387392Z digest=sha256:f504ee5fd4a11762a5f43abd692ddf5ba043f8f975bfa92df88b0ddda99e6c8a

Observation af9c054d-6b21-4ece-ad49-5339ec924b39 · outbound

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

What to Keep and What to Drop: Adaptive Table Filtering Framework Open-WikiTable: Dataset for Open Domain Question Answering with Complex Reasoning over Table

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:40.497324Z digest=sha256:101ea3a76841e8c4f7ece5925691d3d2b4849da1eb23d3e00011c1b6c2685172

Observation c9a9963f-7d82-499f-9c13-ca39e81ab44c · outbound

This paper cites Open-wikitable: Dataset for odqa with complex reasoning over table.

What to Keep and What to Drop: Adaptive Table Filtering Framework Open-wikitable: Dataset for odqa with complex reasoning over table

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:43.565032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.564440Z digest=sha256:1dfac27ff8cd07d48808992eafe220f9054f678f62ac0a0ad1c0fd3d1526f6ae

Observation 03c69015-aef7-4f72-a7be-d38ab1c05e1b · outbound

This paper cites BART : Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension.

What to Keep and What to Drop: Adaptive Table Filtering Framework BART : Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension

Reference 16

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no resolver link, observed 2026-08-06T21:47:40.647213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:40.647213Z digest=sha256:325e1294cd3fd6adc2907b56d59b7b53299dca1b039316aed155e501e8c82237

Observation 17ba75ed-0d45-4710-a91e-778e22250caf · outbound

This paper cites TAPEX: Table Pre-training via Learning a Neural SQL Executor.

What to Keep and What to Drop: Adaptive Table Filtering Framework TAPEX: Table Pre-training via Learning a Neural SQL Executor

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T21:47:40.700778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:40.700778Z digest=sha256:eea227a38e9b8e10f3cf3c0766a2dd15db711d0f5308893b45bd74bcdb27b456

Observation a7fcb26e-3fe5-40f1-9a46-b2105a81bbf1 · outbound

This paper cites Interpretable LLM-based Table Question Answering.

What to Keep and What to Drop: Adaptive Table Filtering Framework Interpretable LLM-based Table Question Answering

Reference 18

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no resolver link, observed 2026-08-06T21:47:40.740194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:40.740194Z digest=sha256:96ab181234c454ace04bc62406cf19837f34503baf67b83470b6e9f4baa89f93

Observation 0ad89bb1-49d9-4a06-8bcc-274cd16a2010 · outbound

This paper cites Gpt-4o: Openai’s new multimodal model.

What to Keep and What to Drop: Adaptive Table Filtering Framework Gpt-4o: Openai’s new multimodal model

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:43.330093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.826976Z digest=sha256:085201e9300f9120314904ef9e16679072805f389486cee6db523efe4746a174

Observation 1dce4282-0213-4034-8a62-ada621ca2b01 · outbound

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

What to Keep and What to Drop: Adaptive Table Filtering Framework Compositional Semantic Parsing on Semi-Structured Tables

Reference 20

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unresolved
no resolver link, observed 2026-08-06T21:47:40.900097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:40.900097Z digest=sha256:55ffe0c6cc2913e168674d3ea8417719df86df14f93f49bbcb9d961d1539323f

Observation 4ea326b3-c9aa-4852-b3d5-f11059ce4a48 · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks.

What to Keep and What to Drop: Adaptive Table Filtering Framework Sentence-bert: Sentence embeddings using siamese bert-networks

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:43.091250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.977762Z digest=sha256:b30996a093abd1cd0cb16a32bab59cf00e375a6ba164d4bcb3f8d6d5f9df6024

Observation 2a478b10-917d-475e-8cad-6647999017ff · outbound

This paper cites Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval.

What to Keep and What to Drop: Adaptive Table Filtering Framework Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:42.974116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:41.053545Z digest=sha256:143258f1c231d63a7ab85f18c04f1d2d7a230a92c6122d8ab4ef41fd2ff10d07

Observation 5986dc10-b587-44c8-8d4e-a33162f9f12f · outbound

This paper cites Silhouettes: a graphical aid to the interpretation and validation of cluster analysis.

What to Keep and What to Drop: Adaptive Table Filtering Framework Silhouettes: a graphical aid to the interpretation and validation of cluster analysis

Reference 23

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no resolver link, observed 2026-08-06T21:47:41.145950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:41.145950Z digest=sha256:a1e1c83efbbfb39f2ca23cff1c86826ff8a514e388c46b0e92ed306fd16c7d63

Observation 7171894c-48dd-44be-9d30-fc18208e32e7 · outbound

This paper cites Unveiling Implicit Table Knowledge with Question-Then-Pinpoint Reasoner for Insightful Table Summarization.

What to Keep and What to Drop: Adaptive Table Filtering Framework Unveiling Implicit Table Knowledge with Question-Then-Pinpoint Reasoner for Insightful Table Summarization

Reference 24

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verified exact
local_arxiv, observed 2026-08-06T21:47:42.412179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:41.223675Z digest=sha256:8badf08dc9dc5347d107db68b6e608ed48bf3bcc5d1f2f771221375aad52b279

Observation a3b24bf7-cfd6-4ec6-b9fd-7c9be1181e7c · outbound

This paper cites Attention is all you need.

What to Keep and What to Drop: Adaptive Table Filtering Framework Attention is all you need

Reference 25

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unresolved
no resolver link, observed 2026-08-06T21:47:41.315064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:41.315064Z digest=sha256:2128709c00820d2369a7b4b8f255b27d43a5b159c42efc46c46513b953ef9856

Observation c9e38d71-a5ab-4758-a627-5636bbc4e110 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

What to Keep and What to Drop: Adaptive Table Filtering Framework Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 26

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unresolved
no resolver link, observed 2026-08-06T21:47:41.390911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:41.390911Z digest=sha256:364a06715f35fc55066a2edd29c62906d8de08f3089679a60dbf337e17e7a65a

Observation c7fa95e3-e1db-4e51-910a-f9a5d9995adf · outbound

This paper cites an unresolved cited work.

What to Keep and What to Drop: Adaptive Table Filtering Framework Unresolved cited work

Reference 27

Resolution
verified exact
doi, observed 2026-08-06T21:47:42.140936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:41.457554Z digest=sha256:c34262b9904659d69630370d30ad6024701c90604a7cca1c6bab535ead609395

Observation eb3de599-ef81-48f0-9a17-59c22f1b6bf4 · outbound

This paper cites Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding.

What to Keep and What to Drop: Adaptive Table Filtering Framework Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T21:47:41.544697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:41.544697Z digest=sha256:c3b619b1b4503cd6abd72e8b56c591bf868e85ec552a070c86965ed14627cdd0

Observation a987729e-b422-4dc5-9248-56f884528ec2 · outbound

This paper cites Protrix: Planning and reasoning over tables with sentence context.

What to Keep and What to Drop: Adaptive Table Filtering Framework Protrix: Planning and reasoning over tables with sentence context

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:47:42.889510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T21:47:41.641075Z digest=sha256:85e79b9aea38b7cc6a98e281232e636b09eb2d2cf9868ff60402eb80b1fe2753

Observation f4dccc7d-63ca-4b1d-9ddb-dcc61a19ec30 · outbound

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

What to Keep and What to Drop: Adaptive Table Filtering Framework Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T21:47:41.706145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:41.706145Z digest=sha256:39c0426a6e36863273e53208360e4c3a22f2a45577023941fc08048aaa77c52b

Observation a6755169-532d-4b14-9fe6-87261a9c2f75 · outbound

This paper cites ALTER : Augmentation for large-table-based reasoning.

What to Keep and What to Drop: Adaptive Table Filtering Framework ALTER : Augmentation for large-table-based reasoning

Reference 31

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unresolved
no resolver link, observed 2026-08-06T21:47:41.781127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:41.781127Z digest=sha256:6c9ad0b944cd5f3966014064c5a478442bb991673fb69c2d320d051cc0a3d415

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

This paper cites ReAcTable: Enhancing ReAct for Table Question Answering.

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:d50225d08901a5b0fed6124788a35f3f5e252134c41a4c36ae832b481933283f

Observation 79cd05e6-0282-4482-b3b5-96963c6e5782 · outbound

This paper cites TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance.

What to Keep and What to Drop: Adaptive Table Filtering Framework TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance

Reference 33

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unresolved
no resolver link, observed 2026-08-06T21:47:41.945165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:47:41.945165Z digest=sha256:b8d826ec84c5f9a8c8e189005d8c674b9b54402ca75d6746b4a41a40802da2be

Pith citing papers

No inbound Pith citation observations are available.