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Paper Citation Record · LEDGER

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models

As of 13 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2411.16002.

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

pith.paper-citation-record.v1
2411.16002 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:42:10.916116Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

20 of 20 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 50a12739-a968-4479-b0aa-5a3dadb49b37 · outbound

This paper cites Qwen Technical Report.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Qwen Technical Report

Reference 1

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no resolver link, observed 2026-08-12T13:42:10.825545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.825545Z digest=sha256:2f43e8972adac4f83e13c2f5aa7ecd729aa3efbc328168f726533c4d349829cb

Observation a6ca1041-7f71-40de-baab-d1d71e401910 · outbound

This paper cites HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data

Reference 2

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unresolved
no resolver link, observed 2026-08-12T13:42:10.830972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.830972Z digest=sha256:eb04b1e1b92483b9cfd0147e45ff083b1844652df7a7f49bdf07597982173d47

Observation 351e91a7-b9af-40b6-b0bd-9c232f5a70a9 · outbound

This paper cites How to think step-by-step: A mechanistic understanding of chain-of-thought reasoning.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models How to think step-by-step: A mechanistic understanding of chain-of-thought reasoning

Reference 3

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unresolved
no resolver link, observed 2026-08-12T13:42:10.835765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.835765Z digest=sha256:23eba39642e646947d08aad30d449fa4d09d9964edb30727de2a031fc1f75f1a

Observation f3b2f3b9-87ec-4f61-9c3a-56481c7083e4 · outbound

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

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 4

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unresolved
no resolver link, observed 2026-08-12T13:42:10.841125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.841125Z digest=sha256:a8a696f5421979e75751bd4370cbc325918582e2ffd25f0b9bec1ffe86b104c1

Observation f8de2f4a-a94b-45ee-b45e-bb8c86faacae · outbound

This paper cites PaLM 2 Technical Report.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models PaLM 2 Technical Report

Reference 5

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unresolved
no resolver link, observed 2026-08-12T13:42:10.845705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.845705Z digest=sha256:ff99aec264f8c28b2e65f7512d39a0d7966a0e4a7d83b57c90d7a4e00e304f8a

Observation 553d18ea-5071-476d-929a-6609567ae1db · outbound

This paper cites Large Language Models Can Self-Improve.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Large Language Models Can Self-Improve

Reference 6

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unresolved
no resolver link, observed 2026-08-12T13:42:10.850405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.850405Z digest=sha256:84fa7611ebd10fdafa16ea980efe5e2a0f30ccf50d0a3f4d44c6545a0c99ad1f

Observation a396b697-34ac-4269-87bc-b15166a6627a · outbound

This paper cites an unresolved cited work.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Unresolved cited work

Reference 7

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unresolved
no resolver link, observed 2026-08-12T13:42:10.855612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.855612Z digest=sha256:0ed5e529f6a54891d2adbef06f7a7b8db3682ac33159e18401f85fa25011a7b8

Observation 2ec0519a-0abc-4d32-88c6-d6d5090b431b · outbound

This paper cites TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T13:42:10.860036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.860036Z digest=sha256:749cde5f715fe9671dfe09028a38c9cd7e111fff0622ba450ca40f74b56ccdea

Observation fabe808e-35e0-4e1b-a206-080c7a860c2c · outbound

This paper cites G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T13:42:10.864783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.864783Z digest=sha256:53a090812fe77ec02f4142856caa3be3eff83e50822c1c9277acf958732a83b3

Observation b477cd16-41ff-4e5a-8ff7-e620397e9039 · outbound

This paper cites GPT-4 Technical Report.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models GPT-4 Technical Report

Reference 10

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unresolved
no resolver link, observed 2026-08-12T13:42:10.869392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.869392Z digest=sha256:d672f490787a8d34f8bc8657103901275afa4321c0ff9184567753ba04263c1f

Observation 2a4a4ee0-03c8-4c03-81c0-b34fc5516844 · outbound

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

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Compositional Semantic Parsing on Semi-Structured Tables

Reference 11

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unresolved
no resolver link, observed 2026-08-12T13:42:10.873853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.873853Z digest=sha256:d92e6f4e35d1d2f9ff6b0b9135c4acc08f602c04b57bfb144bcee05f5ed492b1

Observation eac56dc8-68e6-416d-8d62-38eaab99e637 · outbound

This paper cites an unresolved cited work.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Unresolved cited work

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T13:42:10.879791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.879791Z digest=sha256:95540a6fd8a6864bbdd3144d283ccfb0ecf9ad7365cd5b10e8a3553e4f9a8800

Observation 87bf950c-6164-4f1b-8432-7afbeda79524 · outbound

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

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-12T13:42:10.883998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.883998Z digest=sha256:94a31bb802b0186e814a6751cb7d29976c342a10396044c9bb96e18864286519

Observation ecc5d42e-401b-40e4-9599-e12f65f1683d · outbound

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

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

Reference 14

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unresolved
no resolver link, observed 2026-08-12T13:42:10.888279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.888279Z digest=sha256:284f3c7c6bee9922c3b0fb89796273b73bf27b012dc08bc1c682a57a93923eda

Observation 8553994c-4008-4726-839d-31de4157bb30 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-12T13:42:10.892833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.892833Z digest=sha256:2ad491828380b3778d45550e50a7143b43b0222bdce7bfabc03378273d37fbf7

Observation 9f38e36f-b1e9-4d08-aa7d-af0e8b1a1b15 · outbound

This paper cites Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Investigating Table-to-Text Generation Capabilities of LLMs in Real-World Information Seeking Scenarios

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T13:42:10.897402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.897402Z digest=sha256:f44c98e3c3d58cfa18dfb246a3aba05b58fc75ba51f934f86f8ec194096e5101

Observation 3452dce9-7734-4518-9cee-0583fe244300 · outbound

This paper cites Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T13:42:10.901881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.901881Z digest=sha256:4765e4dab421ef53094e61f9c393600e538e1582b56012428df6ebe7ccc0f40e

Observation 03f39fa5-4bc7-4d2c-9946-8ca19fb14838 · outbound

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

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance

Reference 18

Resolution
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no resolver link, observed 2026-08-12T13:42:10.906249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.906249Z digest=sha256:8a735f31a66f3888ecf669a2626fe1845821e8fa98ffac35f655fef0a8afb9ef

Observation 8aeb60df-2214-49ee-ae2e-044f14cefe1f · outbound

This paper cites online" 'onlinestring :=.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models online" 'onlinestring :=

Reference 19

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unresolved
no resolver link, observed 2026-08-12T13:42:10.910972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.910972Z digest=sha256:d28fa94fe3b102045b6f3dc62c755bb756e2191904f91d11db7eca14e5c7dfae

Observation c63defe6-79eb-47e6-befb-361c23329ad0 · outbound

This paper cites write newline.

Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models write newline

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-12T13:42:10.916116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:42:10.916116Z digest=sha256:74efcc7747a2b6689a349db27ad87a80993b2f910d52085344858d86e676b951

Pith citing papers

No inbound Pith citation observations are available.