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Paper Citation Record · LEDGER

Rethinking Table Instruction Tuning

As of 11 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 1 inbound Pith citation observation for arXiv:2501.14693.

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

pith.paper-citation-record.v1
2501.14693 v4

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:59:58.663292Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:03:43.410678Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T06:03:57.334781Z

Reference resolution

60 of 60 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved56
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 96e8b386-9f57-4a52-8a1e-983b1f99b69a · outbound

This paper cites URL: " 'urlintro :=.

Rethinking Table Instruction Tuning URL: " 'urlintro :=

Reference 1

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no resolver link, observed 2026-08-10T14:59:58.367641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.367641Z digest=sha256:be1f5a0b37a5a758704b9cad941148adb1bc6c231d393e0d21f3ae325da425ae

Observation c0601fd9-68a0-4e57-a005-4b187fdf3ed4 · outbound

This paper cites write newline.

Rethinking Table Instruction Tuning write newline

Reference 2

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source=arxiv_source observed=2026-08-10T14:59:58.373513Z digest=sha256:29da85316657dc28eccbf20a4c5458a0a7771426bdc6942300f4af4be3a7abc0

Observation 2a6d0870-c0f9-4ee9-b2be-93dc6e8ea6b9 · outbound

This paper cites write newline.

Rethinking Table Instruction Tuning write newline

Reference 3

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source=arxiv_source observed=2026-08-10T14:59:58.379297Z digest=sha256:110bd4b9d52a931c4cbe58e078f4217b834354bfff36473aee7ebca2752cf6d6

Observation 0c7641cf-3874-4296-9d40-80c4fac905b3 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Rethinking Table Instruction Tuning Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 4

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source=arxiv_source observed=2026-08-10T14:59:58.384647Z digest=sha256:220f476b49ff0634b4e9715c937270476f395e6404aecd366484a89dddd41adf

Observation 7f377886-1c09-4305-97b4-4885a8a9bffe · outbound

This paper cites GPT-4 Technical Report.

Rethinking Table Instruction Tuning GPT-4 Technical Report

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.389703Z digest=sha256:1f654f1468d2d60ea1b74724b3572bfc922ce2f07dbc45c5c3347855b798782a

Observation 57fdcb65-cf4f-4ff9-8359-d1a04c09409d · outbound

This paper cites The fact extraction and VER ification over unstructured and structured information ( FEVEROUS ) shared task.

Rethinking Table Instruction Tuning The fact extraction and VER ification over unstructured and structured information ( FEVEROUS ) shared task

Reference 6

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T14:59:58.394250Z digest=sha256:a9758697c88b2e95beb733864fa969970c08692cf84ae1e23870e54b9b6f8a61

Observation 412069e0-fe83-4035-8159-2f67e57ab74a · outbound

This paper cites Qwen Technical Report.

Rethinking Table Instruction Tuning Qwen Technical Report

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.399360Z digest=sha256:79fd72bcd7ed8779ea89d8ad3c9d5ba4e1790fd0caa883240f26dcad1b375c80

Observation 11948538-93c6-49a2-b3f7-62ce8b015ddf · outbound

This paper cites How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings.

Rethinking Table Instruction Tuning How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings

Reference 8

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.404418Z digest=sha256:64c5a14bc96112751b3c840e82c8076b6c94c9db7b24e941407c624fe4bfaf95

Observation b4bfff87-87b5-4012-a694-ae69b1a713b5 · outbound

This paper cites TabFact: A Large-scale Dataset for Table-based Fact Verification.

Rethinking Table Instruction Tuning TabFact: A Large-scale Dataset for Table-based Fact Verification

Reference 9

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source=arxiv_source observed=2026-08-10T14:59:58.409089Z digest=sha256:53621cb36f810b6a76b6dae0a1fc6174383eb868465b4d7550adff8de8eab224

Observation f6340280-e65f-4c16-a882-70b45aae325f · outbound

This paper cites H ybrid QA : A dataset of multi-hop question answering over tabular and textual data.

Rethinking Table Instruction Tuning H ybrid QA : A dataset of multi-hop question answering over tabular and textual data

Reference 10

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T14:59:58.414151Z digest=sha256:787e587799bf98cb2d27851f511efa683989720791e4d32b0af1bac5917ea360

Observation 74e624f1-4e5e-4b54-be5c-ae76a9b35f45 · outbound

This paper cites H i T ab: A hierarchical table dataset for question answering and natural language generation.

Rethinking Table Instruction Tuning H i T ab: A hierarchical table dataset for question answering and natural language generation

Reference 11

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source=arxiv_source observed=2026-08-10T14:59:58.419032Z digest=sha256:36ac438551d72df1d270c29bbe2027589f8ef8c19a08281daa6d781d3e0dd8f4

Observation 0ceee8c1-5de8-41fc-9adb-f9fecfe478fa · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90\ See https://vicuna.

Rethinking Table Instruction Tuning Vicuna: An open-source chatbot impressing gpt-4 with 90\ See https://vicuna

Reference 12

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source=arxiv_source observed=2026-08-10T14:59:58.423985Z digest=sha256:c7be7652be999f4646d0826fdd21a38fbc6076a41b03bdb4c8178dfff8be7e79

Observation f2ee7d09-a517-4eb9-bdc8-213e8ff52175 · outbound

This paper cites Scaling instruction-finetuned language models.

Rethinking Table Instruction Tuning Scaling instruction-finetuned language models

Reference 13

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.428689Z digest=sha256:963676c68cd7d4bf7391ed90bac2fece6612ec611c76e69be34c107750da643d

Observation d88237cd-e71f-4568-9bef-74524daf5753 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Rethinking Table Instruction Tuning Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 14

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no resolver link, observed 2026-08-10T14:59:58.433443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.433443Z digest=sha256:e6bc8c53f0167ac72d900c11aa194ace301f5c946e5d12d7bce78d0709e15619

Observation 39d86cca-52bd-4069-a526-cd041f6e33a1 · outbound

This paper cites Tables as texts or images: Evaluating the table reasoning ability of LLM s and MLLM s.

Rethinking Table Instruction Tuning Tables as texts or images: Evaluating the table reasoning ability of LLM s and MLLM s

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:59:59.675490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:59:58.438203Z digest=sha256:07a53752a626a3d37ec1f8d85587b662546701d90c90f7ced4a391afa49a197e

Observation cfa9fc99-f883-44f5-9251-c28d35937bf9 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

Rethinking Table Instruction Tuning Qlora: Efficient finetuning of quantized llms

Reference 16

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.442816Z digest=sha256:0c60e32c29c3d8280b7a6d648f320dd7d7e54f38926418d8212d969ad6e76c88

Observation 82bde568-04c7-4adb-8227-11cf5bd87793 · outbound

This paper cites BERT : Pre-training of deep bidirectional transformers for language understanding.

Rethinking Table Instruction Tuning BERT : Pre-training of deep bidirectional transformers for language understanding

Reference 17

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no resolver link, observed 2026-08-10T14:59:58.447416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.447416Z digest=sha256:712c42074f26e4775f34ed0201c7b596faa1c88e10e9a81a9404bbd0d8e2d6f0

Observation b267509e-aa7e-447e-b71a-c507c1586e42 · outbound

This paper cites The Llama 3 Herd of Models.

Rethinking Table Instruction Tuning The Llama 3 Herd of Models

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.451560Z digest=sha256:1d7a5c085013afa76090e568dd3535cfa5fe2625bf20e589b89f8339532d4aee

Observation d3b92195-61c8-4822-869f-91626925cfec · outbound

This paper cites Key-Value Retrieval Networks for Task-Oriented Dialogue.

Rethinking Table Instruction Tuning Key-Value Retrieval Networks for Task-Oriented Dialogue

Reference 19

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source=arxiv_source observed=2026-08-10T14:59:58.456823Z digest=sha256:6d2887a9d1bf4aab27c4eb7b8ddf77a4869c1a2775e31dda9f4d2b806e16dc26

Observation 4f32118a-6241-4daf-b95d-740fc17cc614 · outbound

This paper cites CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing.

Rethinking Table Instruction Tuning CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

Reference 20

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T14:59:58.461595Z digest=sha256:cdea0d02e87fbfb843ff30834e647c35c1b22f3ba086247cdaf8c0c9ffdee401

Observation a3e61928-7e4b-41d8-89dc-e5c3a8be2d93 · outbound

This paper cites INFOTABS : Inference on tables as semi-structured data.

Rethinking Table Instruction Tuning INFOTABS : Inference on tables as semi-structured data

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.466589Z digest=sha256:b00f53a64d0cf3f0d743637a4646fced88784a2bfb24df6b0ef85cd11cc65779

Observation bfe465ec-c4bc-4c25-b581-0e9d156af821 · outbound

This paper cites Measuring massive multitask language understanding.

Rethinking Table Instruction Tuning Measuring massive multitask language understanding

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.471485Z digest=sha256:d8e442bf721c147d7ee7da19e9a9217af2374735e91e2206e810c548d9231d77

Observation 029eae3f-05c1-4987-b7ba-86af5ab6e2ac · outbound

This paper cites T a P as: Weakly supervised table parsing via pre-training.

Rethinking Table Instruction Tuning T a P as: Weakly supervised table parsing via pre-training

Reference 23

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.476243Z digest=sha256:813573431d15719c3415dec7d8e2b0d1341b6c716419389b5a8b63b1950a2767

Observation fde0f27f-3588-417e-af9d-84f9cedd6255 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Rethinking Table Instruction Tuning LoRA: Low-Rank Adaptation of Large Language Models

Reference 24

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source=arxiv_source observed=2026-08-10T14:59:58.480909Z digest=sha256:ad0bb3b856404b8ab9488a01155eb9e36d0047a6bfe4e2020d308e87654b366e

Observation 65965349-b386-4502-be28-5299681c3f7d · outbound

This paper cites Mistral 7B.

Rethinking Table Instruction Tuning Mistral 7B

Reference 25

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.485430Z digest=sha256:8262f18fe91656ccc848dad3b75501dafee14a3dc377007efaa0995e74244a90

Observation 39fadb3f-6fe1-4eef-9b4b-43ee48745a64 · outbound

This paper cites AIT-QA : Q uestion answering dataset over complex tables in the airline industry.

Rethinking Table Instruction Tuning AIT-QA : Q uestion answering dataset over complex tables in the airline industry

Reference 26

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source=arxiv_source observed=2026-08-10T14:59:58.490569Z digest=sha256:a709d87ac9592ebc95c4874b5ff014cccbca6d0c46089337ab065e9e1d1596fe

Observation 27717b3f-c4e8-4cf9-82ed-c3466f4093e7 · outbound

This paper cites Neural text generation from structured data with application to the biography domain.

Rethinking Table Instruction Tuning Neural text generation from structured data with application to the biography domain

Reference 27

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source=arxiv_source observed=2026-08-10T14:59:58.495596Z digest=sha256:d60c229b23eb54170c8bc913fcb885a985fb4ba20841a6600cbaddc5e8e78aa1

Observation e3915953-0c50-4bed-8830-ef50fc4e4409 · outbound

This paper cites Table-GPT: Table-tuned GPT for Diverse Table Tasks.

Rethinking Table Instruction Tuning Table-GPT: Table-tuned GPT for Diverse Table Tasks

Reference 28

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.500992Z digest=sha256:7235f5f81e5cbca81d8f6cc9f7b76994382a1767f5e93134c65b4eae1376b6df

Observation 42ee9c59-be55-4566-b23d-81de7b1835ae · outbound

This paper cites Table-to-text generation by structure-aware seq2seq learning.

Rethinking Table Instruction Tuning Table-to-text generation by structure-aware seq2seq learning

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:59:59.627694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:59:58.505884Z digest=sha256:dec4405a08df7a94063f0bd4efe5db444fb15c3a9c6a2b3c596bc315d8f707d9

Observation f85a8118-77e2-4a22-9063-bc1773eff1fb · outbound

This paper cites Dynamic prompt learning via policy gradient for semi-structured mathematical reasoning.

Rethinking Table Instruction Tuning Dynamic prompt learning via policy gradient for semi-structured mathematical reasoning

Reference 30

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.510606Z digest=sha256:f6c94f9775f7b4c052ed610121257d3cdd23dff72a7b6eb477866ddda876e5fe

Observation 649fd74e-db73-4d0d-af9c-583a7a9d5b2c · outbound

This paper cites F e T a QA : Free-form table question answering.

Rethinking Table Instruction Tuning F e T a QA : Free-form table question answering

Reference 31

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no resolver link, observed 2026-08-10T14:59:58.515318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.515318Z digest=sha256:ed2186aeb35ae8b9c1a7c35e04f89850bbdea50c9e0d5c3c0f024c261187bb80

Observation 54b97192-fe0f-40f3-a955-20d010da747c · outbound

This paper cites ToTTo : A controlled table-to-text generation dataset.

Rethinking Table Instruction Tuning ToTTo : A controlled table-to-text generation dataset

Reference 32

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.520110Z digest=sha256:6ef6d77942ad817d317ed20b9ab1746fb31c719ca8283ecb7ba642b50a9e3171

Observation 30ab07de-dac0-4acf-b5f1-0ab26aa39a07 · outbound

This paper cites Compositional semantic parsing on semi-structured tables.

Rethinking Table Instruction Tuning Compositional semantic parsing on semi-structured tables

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.524898Z digest=sha256:59b666803c7305956ccdeefc09c4a80ebe6b1410a0d7f0502ce4cf6b969e2fcf

Observation 411c5b93-cb2e-449c-9804-0deda9d2031b · outbound

This paper cites Qwen2.5 Technical Report.

Rethinking Table Instruction Tuning Qwen2.5 Technical Report

Reference 34

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no resolver link, observed 2026-08-10T14:59:58.529635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.529635Z digest=sha256:ce5fdf29502baef76a8c9d3c170a1999a1e86b69913befe52ff9346e248bb043

Observation 34dc890b-8f17-4612-9d69-1a9e6ef4674c · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

Rethinking Table Instruction Tuning GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 35

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no resolver link, observed 2026-08-10T14:59:58.534356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.534356Z digest=sha256:e607d0120239ad055a4f1663a74e537ea622c6ad6399e2763b21fc7bf5123a26

Observation c966cd12-fa7f-4fdd-9f26-ffdb3b8e4d71 · outbound

This paper cites Assessing llms' mathematical reasoning in financial document question answering.

Rethinking Table Instruction Tuning Assessing llms' mathematical reasoning in financial document question answering

Reference 36

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no resolver link, observed 2026-08-10T14:59:58.538899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.538899Z digest=sha256:1636aa52586445e503db9615a47dd1f41d9e027bfe47851271f2ec119470b937

Observation af3be644-c0c9-4540-bfd3-a6aa1b03d07f · outbound

This paper cites TableGPT2: A Large Multimodal Model with Tabular Data Integration.

Rethinking Table Instruction Tuning TableGPT2: A Large Multimodal Model with Tabular Data Integration

Reference 37

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no resolver link, observed 2026-08-10T14:59:58.543109Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.543109Z digest=sha256:b49b45633c900c210f13545ac27fde866869c62efab249913f45355ce94c5383

Observation e256fce7-0d3b-416d-8eab-5d2d99d601c1 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Rethinking Table Instruction Tuning Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 38

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no resolver link, observed 2026-08-10T14:59:58.548023Z

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source=arxiv_source observed=2026-08-10T14:59:58.548023Z digest=sha256:956d83336d11ef39ec8eecc699418ccf18f489d8ae146cc7da9b2d14a628d64c

Observation 60c5a44b-e9dc-45b9-990b-6b1e2eb6e3b5 · outbound

This paper cites MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark.

Rethinking Table Instruction Tuning MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.553046Z digest=sha256:f3c44774190b9b4e6c98287e1ed3979bc98ea9120e1347bd81ac146c0fdadb5d

Observation 2c4fcea9-c720-4b91-94b4-3138b344da81 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Rethinking Table Instruction Tuning Chain-of-thought prompting elicits reasoning in large language models

Reference 40

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T14:59:58.558135Z digest=sha256:51697d984563bbc0908486f274962232f9294ce57b68d8b9e01ce5f69bdb0ae2

Observation 423b7eac-1f98-462e-96a4-19acc45ffdcc · outbound

This paper cites TableBench: A Comprehensive and Complex Benchmark for Table Question Answering.

Rethinking Table Instruction Tuning TableBench: A Comprehensive and Complex Benchmark for Table Question Answering

Reference 41

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.563072Z digest=sha256:888403b3a4edcebaa177b1daddc35d118375ed06bfb8f6ad15d940c249282b52

Observation 4387817f-a8f0-49c8-afb2-db6e9fe143c1 · outbound

This paper cites Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A.

Rethinking Table Instruction Tuning Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A

Reference 42

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no resolver link, observed 2026-08-10T14:59:58.568026Z

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source=arxiv_source observed=2026-08-10T14:59:58.568026Z digest=sha256:6e815e2bef0e0bf0c9cb8d9c9060025f9f6fa9df346c3d8344abee91bd370c75

Observation 1cc6fb3c-424f-46eb-8b51-0629fc8728ad · outbound

This paper cites Mmtu: A massive multi-task table understanding and reasoning benchmark.

Rethinking Table Instruction Tuning Mmtu: A massive multi-task table understanding and reasoning benchmark

Reference 43

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no resolver link, observed 2026-08-10T14:59:58.574159Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T14:59:58.574159Z digest=sha256:ea4d303523db942ce704693a5f4f59beca48ccac5837194ec5ad0e2edab7617b

Observation d8cf8a38-e461-499a-8d59-4699d229e4a2 · outbound

This paper cites Qwen3 Technical Report.

Rethinking Table Instruction Tuning Qwen3 Technical Report

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.579539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.579539Z digest=sha256:af4d0da32730e0b0355177d3d56a9a9e307ea5ae9a388ddd0c412781aac7833e

Observation d2c5db91-36f3-4bfe-916c-75c418ebff3e · outbound

This paper cites T able F ormer: Robust transformer modeling for table-text encoding.

Rethinking Table Instruction Tuning T able F ormer: Robust transformer modeling for table-text encoding

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.585768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.585768Z digest=sha256:54cf0f3da7fe39b4991bd7eb19a009862b03e0779fc6a94084351efef3575324

Observation 01bc38b5-44ad-4205-b69c-20442019f37a · outbound

This paper cites Table-r1: Inference-time scaling for table reasoning.

Rethinking Table Instruction Tuning Table-r1: Inference-time scaling for table reasoning

Reference 46

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no resolver link, observed 2026-08-10T14:59:58.591622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.591622Z digest=sha256:4b3f43f12777ed7c3d5e25c9bf59ed2535d879195f85634e5eb655fd318d5219

Observation d5180eba-2f33-4e16-9743-9cb77185969d · outbound

This paper cites T a BERT : Pretraining for joint understanding of textual and tabular data.

Rethinking Table Instruction Tuning T a BERT : Pretraining for joint understanding of textual and tabular data

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.596540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.596540Z digest=sha256:60bb7bd7336ac6f303a0e702c5c3ecd83d9cbba695752ee73e5417e5be198739

Observation ea8540d0-064e-4ab6-91c3-a3967ca26649 · outbound

This paper cites TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT.

Rethinking Table Instruction Tuning TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.601747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.601747Z digest=sha256:fd49f43c5c3fe83f9d5428c1ccab5f192778056e13450483447648d7e2920d5d

Observation 7c70a6b9-f587-4cbf-806b-2ec792b0884b · outbound

This paper cites T able L lama: Towards open large generalist models for tables.

Rethinking Table Instruction Tuning T able L lama: Towards open large generalist models for tables

Reference 49

Resolution
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no resolver link, observed 2026-08-10T14:59:58.606794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.606794Z digest=sha256:f5f1182bbad81133e59673e03572ef3845ea4ddd0df320a59de413d54cfd6445

Observation 578a8150-7809-4646-8674-4b3a0a7e1197 · outbound

This paper cites TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios.

Rethinking Table Instruction Tuning TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.611787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.611787Z digest=sha256:732842d4721ca239c8f2cd605aeaa501d730b7cfac92f1d120b727293cb3c13b

Observation c954a82d-bd28-4dbb-bae8-9e1c8a0b6025 · outbound

This paper cites Multimodal table understanding.

Rethinking Table Instruction Tuning Multimodal table understanding

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:59:59.578809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-08-10T14:59:58.618201Z digest=sha256:1b75a06ccc77ffbd4d2c97ea895749462d8bc2ad58b71aff109ac7d80e5b5b58

Observation d6f0366d-7961-42b6-9b05-8c2238137d35 · outbound

This paper cites L lama F actory: Unified efficient fine-tuning of 100+ language models.

Rethinking Table Instruction Tuning L lama F actory: Unified efficient fine-tuning of 100+ language models

Reference 52

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no resolver link, observed 2026-08-10T14:59:58.623595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.623595Z digest=sha256:ee110ee54d91f0bc21643f5e094212805d668f62a151ff97dfa871950b3b67e0

Observation a68c9f11-79b6-4cb5-a7df-8323fb0031c0 · outbound

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

Rethinking Table Instruction Tuning Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 53

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no resolver link, observed 2026-08-10T14:59:58.629136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.629136Z digest=sha256:ed0dd554c434e4fe2c3d852ef5c6783aecf676afd37ad6a23787f895aed5cf43

Observation ec1322b3-c36f-4882-980b-672a3e633931 · outbound

This paper cites Lima: Less is more for alignment.

Rethinking Table Instruction Tuning Lima: Less is more for alignment

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.634125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.634125Z digest=sha256:fbc72ce4fb5aade16ed3c3a19358754d28faae0dbf01919dbbabc0d84adf8327

Observation 1db4ff07-2c9c-4735-8f64-faae5bb1b352 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Rethinking Table Instruction Tuning Instruction-Following Evaluation for Large Language Models

Reference 55

Resolution
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no resolver link, observed 2026-08-10T14:59:58.638716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.638716Z digest=sha256:2ce8149baf0515d2b527e6c299e4c74c8dd67b6019d826aca3f10d19e3db4e00

Observation b7814380-3811-46d0-b8e0-6f4e00680d97 · outbound

This paper cites TAT - QA : A question answering benchmark on a hybrid of tabular and textual content in finance.

Rethinking Table Instruction Tuning TAT - QA : A question answering benchmark on a hybrid of tabular and textual content in finance

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.643660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.643660Z digest=sha256:9c74d5a36d6efd73e7e83cd7ae160c7ab5fd139d9f87dd066b5acd7755a4e0d3

Observation 8120f81b-9326-490d-9d1a-402af4e00f12 · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Rethinking Table Instruction Tuning Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.648529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.648529Z digest=sha256:22f396c962e3e4dd108dfd59ae772308b09f0b11a56d240b7d1e71a4c254f21e

Observation 196a251f-30c2-418e-a8df-843dc7a01dea · outbound

This paper cites @esa (Ref.

Rethinking Table Instruction Tuning @esa (Ref

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.653313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.653313Z digest=sha256:e7a9d07d5c92d52174546d9d69702083e648ec8c5202cb89f4af1d08df33e463

Observation 681c4cdb-540b-4e1e-991c-28e4a72e6e95 · outbound

This paper cites an unresolved cited work.

Rethinking Table Instruction Tuning Unresolved cited work

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.658293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.658293Z digest=sha256:6e816f0360675a052322115d8eebc3e206b8e35882277aa0172b77db8a79aaa0

Observation 8894936b-fb43-40b6-848f-33e94f74306c · outbound

This paper cites an unresolved cited work.

Rethinking Table Instruction Tuning Unresolved cited work

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T14:59:58.663292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:59:58.663292Z digest=sha256:1bfae094dc4dfc4f6059c1cda73b19b6144f048c554827e130be046bf39e02f9

Pith citing papers

Observation 6f031d59-c76c-4ae1-bae5-e6c18461f837 · 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 Rethinking Table Instruction Tuning

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-07T06:03:57.412504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T06:03:43.410678Z digest=sha256:7c16b92ad323b79c75d2795bae53220281424cb3ebef86f48a22d6a1892ca24f