Paper Citation Record · LEDGER

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models

As of 7 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 2 inbound Pith citation observations for arXiv:2506.18421.

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

pith.paper-citation-record.v1
2506.18421 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:20:04.057694Z

measured 36 of 36 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T22:18:45.189576Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T14:05:46.699261Z

Reference resolution

34 of 34 outbound references displayed

verified exact1
verified fuzzy5
unresolved28
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4b3a2a05-58ce-4e41-97c9-b4b49af9becd · outbound

This paper cites GPT-4 Technical Report.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:00.709832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 338be5f1-e943-4a6f-8e59-060ada6d38a0 · outbound

This paper cites Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.001340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5a0899b-0996-452e-a24a-0004dc95ce6a · outbound

This paper cites R., et al.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models R., et al

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:05.462141Z

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.

Observation 4744b0a9-e1cc-423d-be1d-4ab347163d09 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Training Verifiers to Solve Math Word Problems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.103215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37bf6e34-0550-4b47-9a1c-d55322eeacbc · outbound

This paper cites RLHF Workflow: From Reward Modeling to Online RLHF.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models RLHF Workflow: From Reward Modeling to Online RLHF

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.350485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da391928-f427-42e1-b027-8a07c6e7404f · outbound

This paper cites The Llama 3 Herd of Models.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models The Llama 3 Herd of Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.408209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27e5dc92-2636-4092-8a11-e867b2856365 · outbound

This paper cites A Survey on LLM-as-a-Judge.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models A Survey on LLM-as-a-Judge

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.489710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8735e25e-e6f3-4e3b-9d82-d8a27040ef97 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.630884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28ca5b0e-bb76-4375-bb69-a5af0144a6fe · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Measuring Mathematical Problem Solving With the MATH Dataset

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.729656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4799446-eba0-46b9-abc3-7b18fee89f36 · outbound

This paper cites Qwen2.5-Coder Technical Report.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Qwen2.5-Coder Technical Report

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.826117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80cd3bb1-90be-4ef7-bb44-8c12aa87e8be · outbound

This paper cites FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:02.097569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d00a86d-a6ac-4f38-ac47-b5ce33ac0601 · outbound

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

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Ait-qa: Question answering dataset over complex tables in the airline industry

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:05.113736Z

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.

Observation 12d33cae-f6e2-4ee8-8fb0-29985d374f4c · outbound

This paper cites TableVQA-Bench: A Visual Question Answering Benchmark on Multiple Table Domains.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models TableVQA-Bench: A Visual Question Answering Benchmark on Multiple Table Domains

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:02.470277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d897cdce-52af-46b2-ac59-5c62e1a1d68f · outbound

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

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:02.598781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa4b1cff-1354-4f94-a1b6-c2ffd55a2a6d · outbound

This paper cites UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:20:04.474776Z

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.

Observation 86b4b131-021c-4617-80dd-67208fb4602b · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:03.205192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdf2d175-1d2b-4802-868a-b97e70998156 · outbound

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

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models TableGPT2: A Large Multimodal Model with Tabular Data Integration

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:03.333517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f6c6654-9fed-443f-8b78-24f80ffffc80 · outbound

This paper cites Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:03.461424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30c8885d-9fdf-40f1-b468-994f82b39700 · outbound

This paper cites MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:03.588865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c82b98e5-bc45-4474-9226-1faf9aee2f94 · outbound

This paper cites Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:03.663026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8ee7cea-3bc6-4461-85a4-b7c960ad444e · outbound

This paper cites Qwen2 Technical Report.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Qwen2 Technical Report

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:03.756297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d44e477d-a053-445e-b0d9-c49b8f7aa476 · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Yi: Open Foundation Models by 01.AI

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:03.872378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5424cf12-9e9c-4ac5-996c-feb3e76872a5 · outbound

This paper cites Spider: A large-scale human-labeled dataset for complex and cross- domain semantic parsing and text-to-sql task.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Spider: A large-scale human-labeled dataset for complex and cross- domain semantic parsing and text-to-sql task

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:04.802096Z

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.

Observation 409a6220-26df-4c16-b46e-06bbdf72dbe6 · outbound

This paper cites BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:04.057694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85074de9-9cc1-4f2f-a4cd-dd4e197a6f2a · outbound

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

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Totto: A controlled table- to-text generation dataset

Reference 2002

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:04.964808Z

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.

Observation 193dd8cc-9d80-4f51-8211-c7db35f3a691 · outbound

This paper cites MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark

Reference 2004

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:02.838439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 111542bc-8bb5-4529-a60e-5f500ef79af2 · outbound

This paper cites TQA-Bench: Evaluating LLMs for Multi-Table Question Answering.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models TQA-Bench: Evaluating LLMs for Multi-Table Question Answering

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:03.071359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7b13eb3-f7c8-4ef6-aa61-1394f2fbae1f · outbound

This paper cites Mistral 7B.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Mistral 7B

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.965467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f7daa07-7220-4925-a7c1-5faf4bcceee0 · outbound

This paper cites McEval: Massively Multilingual Code Evaluation.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models McEval: Massively Multilingual Code Evaluation

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:00.861149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf0866df-e83f-417e-ba0d-bdbccb941bb4 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:01.190008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48d2a58e-7701-44fd-a6bd-4891431660d6 · outbound

This paper cites Table Foundation Models: on knowledge pre-training for tabular learning.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Table Foundation Models: on knowledge pre-training for tabular learning

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:02.370073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d4d8fcb-ca5b-4c36-b977-d8630df5f8ee · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:00.771769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84d11dd7-80f8-4fce-929c-67c01f7d8945 · outbound

This paper cites an unresolved cited work.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:20:05.669312Z

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.

Observation c8c641df-fc1f-43b5-ae47-b30e5d7f0afa · outbound

This paper cites Tables as texts or images: Evaluating the table reasoning ability of llms and mllms.

TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models Tables as texts or images: Evaluating the table reasoning ability of llms and mllms

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:05.289155Z

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.

Pith citing papers

Observation 014cfda9-bca4-4b8a-98b3-9f9f3905be6e · inbound

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows cites this paper.

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-22T00:22:12.404705Z

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.

Observation 5dad171a-f708-44a9-9e65-1a3ab37af9d1 · inbound

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows cites this paper.

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-22T00:22:12.404705Z

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.