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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:39.325490Z digest=sha256:533b1ff0aab3959d90e48992f1b5585e6e34ccb64006a45ce14326c938bef53a

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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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=sha256:97a9a537563e30dbbdfca296d6b6baccd20a92c5c6750fe0e819246939d5a5b0

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 2026-08-08T06:32:00.761636+00:00.

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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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:39.598304Z digest=sha256:597a3eb64eb750c956925c7d609a4102f5b4963de28e0633e28f3b5394163242

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=sha256:39b5e9c304878decf3694caee7e43812f117c5cc9da48385f33a46159e267e9d

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:39.793239Z digest=sha256:c22d860e0fe67588971be12d823b85229d72771f5067efc545c52ba44053659e

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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unresolved
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=sha256:22413eb064b79a77cf54ac87e29ff1fa241ebf9cf344746fb5f3a96aff6ea4a9

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:39.964324Z digest=sha256:da24b7e5847fecf73d5c1da0ac1478ded6ba0bc6314ff0953de1a8cc9967f884

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.057294Z digest=sha256:c2d79e6f5db3b1d2aa64d8473db45c30953145c109940e7f37c414280f26f363

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.171219Z digest=sha256:5c7914230dc9684fef9d999d81a0d0e81916a25b078f8a6f979cc7a1b24ef064

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

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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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.243072Z digest=sha256:718777c5734a9f0cf64340d867cd54e488fb9f5fcb012088a480d312359c0137

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.323666Z digest=sha256:5d475c1ffa2564cc328522f710fcdf730b209dd429cf3da3926efdfb5b2fd407

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.387392Z digest=sha256:cc5d5f0485a95ab69f68be073df3c7aba541334862bcb3de27abf96ab2b87d59

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:ada8b0bb1875317fc79a31814ef59ae224d23f0ddf2cac3ba5127a35aa0b3c86

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.564440Z digest=sha256:23e394f393582da710ee685e91295cf835d32f96a50603ca1c55d242a4bb4492

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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unresolved
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=sha256:939e24bd12b3696544b8149f8bd2d56c87e9e71df48c50b3ccd91e5eb01ab11f

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:c8b693c0e3662bea366b649360249f1cf30a0bbe8b74c5729bfdaf647a177fe5

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=sha256:37f4409cc07148908063263ec3ed14cc6fa0f26c1c825ee0cbcb9fa7fc69591a

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.826976Z digest=sha256:d6efd4a773d5a46603b659c1b29ab9f3c88cdbf3975ddd03d24d729e51036b0b

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=sha256:2322ecba0e89eb7d61e4ce2d0350af8a8b8a16912e0099636e5e0593f278c0ae

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:40.977762Z digest=sha256:ce2cad44bf19e1615114e9b5621bf4ea5126044f475accf7f615b1724ac356a0

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:41.053545Z digest=sha256:92a629b8842c3089fcf8545bebacf9fd5b5351decc45e03fa7016b7d77c349f1

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=sha256:2edd1799a77f2327001c0f76a0b45dae945109023866c811cdff52bd8957d866

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:41.223675Z digest=sha256:cbb944eb4b9697c3e836a1122ed8ea8d408a81a9a51a39105e5dbb2bb86013e4

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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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=sha256:036b040fd5a60a1447730abd68f3681a10f7b617d69e4bfbfc82d843e5c684e2

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=sha256:7251cc9d4d20ede21c78704b338f2f2268b26e19baba05e2f8a5ce6277fbec9b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:41.457554Z digest=sha256:9d8fc4fd3982156d826b5cf0c2f6dc99725a769e6683bba54402ea4f5b48fd29

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=sha256:3b6136df267e206ddbafe293eb8213dc7b890968a94c7a3cb192a111f0add515

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T21:47:41.641075Z digest=sha256:a54781f8bba080ff4d7376c7c2f50d40bc694f3004ea5b4b496856f6def59610

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=sha256:749cd0f624c60bc910e16001e1a13c16ee24cec1ef15a072828d78ce4ae849d5

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=sha256:6a22912c3b91a46565061204ac19e067ef854a68be441ff600e133c20cdeb6b8

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

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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=sha256:6037462b27344460c22abde0995faa1df4c26dfc345a40a3949343f4304ae359

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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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:e7221bde61a14fc34368569a1582f6197d5d7461f01c6eff15be0c7d55012c83

Pith citing papers

No inbound Pith citation observations are available.