Table Reasoning Datasets

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1 paper in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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How AI Coders Discuss, Disagree, and Reach Consensus: Challenges and Opportunities for LLM-Based Qualitative Coding
Sep 12, 2026Jeongyeon Kim, John MitchellQualitative Research Coding Agents
Stanford University, Stanford, CA, USA
Relational Task Generation Language: A Declarative Specification Framework for Relational Deep Learning
Sep 1, 2026Oleksii Kolesnichenko, Jakub Peleška, Gustav ŠírRelational Deep Learning Table Reasoning Datasets
Czech Technical University in Prague, Karlovo náměstí 13, Prague, 121 35, Czechia
SPARK: Skeleton-Guided Reasoning Synthesis from Large-Scale Scientific Literature
Aug 31, 2026Yu Li, Wei Li, Xin Gao +4Table Reasoning Datasets Scientific Discovery
Shanghai AI Laboratory · University of Science and Technology of China · 1Shanghai AI Laboratory 2University of Science and Technology of China +5
Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training
Aug 5, 2026Damien Sileo, Valentin Lacombe, Dimitri KachlerTable Reasoning Datasets Procedural
Univ. Lille, Inria, CNRS, Centrale Lille, UMR 9189 - CRIStal, F-59000 Lille, France
Gram-Space: Structure-Preserving Codebook Compression for Memory-Efficient Neuro-Symbolic AI
Aug 2, 2026Weilun Wang, Wantong LiNeuro-Symbolic Framework Codebooks
University of California, Riverside
PluRel-to-RDB-PFN: Schema-Guided Synthetic Relational Pretraining
Jul 31, 2026Mohammad Sadeq Abolhasani, Viswanath GanapathyPretraining Synthetic Data
SAP Labs, LLC., Palo Alto 94304, United States.
Curriculum Matters: Data-Efficient Relational PFN Pretraining with Synthetic Data
Jul 31, 2026Mohammad Sadeq Abolhasani, Viswanath GanapathyTabular Prior-Data Fitted Network Table Reasoning Datasets
SAP Labs, LLC. Palo Alto, CA, United States
ERUnderstand: Evaluating Vision-Language Models on Structured ER Diagrams
Jul 27, 2026Ali Ansari, Yasmin Mohammadi, Farnoush Nili +3Diagrams Schema
Temple University · Department of Computer and Information Sciences · Philadelphia, PA, USA
Chess_db: A framework for working with large chess game datasets
Jul 23, 2026Nicos Angelopoulos, Jan WielemakerChess Large Databases
University College & Imperial College, London UK · University College & Imperial College London, UK · SWI-Prolog solutions +1
Auto-Fill: Learning to Predict Missing Values Accurately with Specialist Language Models
Jul 22, 2026Yurong Liu, Yeye He, Haoyu Dong +4Auto Research Table Reasoning Datasets
New York University · Microsoft Research
RF-Agent: A Practical Framework for Building Language Agents for RFIC Design
Jul 21, 2026Yueqi Xing, Houbo He, Jolie Wang +5Table Reasoning Datasets Electronic Design Automation
ECE Department, Rice University, Houston, TX, USA · ECE Department, The George Washington University, Washington, D.C., USA
Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Models
Jul 15, 2026Zhuoyuan Fu, Zeshang Li, Yiqiong Zhang +53D Spatial Reasoning 3D Medical Image Segmentation
University of International Relations, Beijing, China · University of Trento, Trento, Italy
ProgramTab: Boosting Table Reasoning of LLMs via Programmatic Paradigm
Jul 13, 2026Pei Guo, Enjie Liu, Yunzhi Tan +6Table Reasoning Datasets LLM Reasoning Strategies
♠Big Data and AI Platform Department, Tencent, China · ♢Institute of Computer Science and Technology, Soochow University, China
PluraMath: Extending Mathematical Reasoning Evaluation Beyond High-Resource Languages
Jul 7, 2026Daryna Dementieva, Nikolay Babakov, Kathy Hämmerl +14Multilingual Benchmark Table Reasoning Datasets
Technical University of Munich (TUM) · Munich Center for Machine Learning (MCML) · Independent Researcher +7
Single and Multi Truth Data Fusion using Large Language Models
Jun 26, 2026Hira Beril Kucuk, Norman W Paton, Jiaoyan Chen +1Global-Local Fusion Framework Uncertainty-Aware Fusion
Department of Computer Science University of Manchester, Oxford Road, Manchester M13 9PL, UK
OracleAnalyser: Analysing Implicit Semantics of Oracle Bone Scripts through MLLMs with Post-training
Jun 24, 2026Zijia Song, Yelin Wang, Zhengyi Ma +5Oracles Table Reasoning Datasets
National University of Defense Technology · ShanghaiTech University · Great Bay University +1
Evolving from Lessons: Skill-Augmented Table Graph Reasoning for Operation-wise Table Question Answering
Jun 20, 2026Guixin Su, Qiankun Pi, Mayi Xu +5Reasoning Graphs Table Reasoning Datasets
School of Computer Science, Wuhan University, Wuhan, China
AudioDER: A Deduplication-Enhanced Reasoning Dataset for Post-Training Large Audio-Language Models
Jun 12, 2026Hui Geng, Yi Su, Han Yin +7Large Audio Language Models Table Reasoning Datasets
College of Computer Science and Technology, National University of Defense Technology Changsha, Hunan, China · Korea Advanced Institute of Science and Technology (KAIST) Korea · Shanghai Jiaotong University Shanghai, China
The Illusion of Multi-Agent Advantage
Jun 11, 2026Prathyusha Jwalapuram, Hehai Lin, Chuyuan Li +7Model-Based Multi-Agent Systems Table Reasoning Datasets
1Salesforce Research. · 2HKUST (Guangzhou). · University of British Columbia. +1
Constructing Evaluation Datasets for Procedural Reasoning: Balancing Naturalness, Grounding, and Multi-Hop Coverage
Jun 11, 2026Sarah Elshabrawy, Rahul K. Dass, Ashok K. GoelFaithful Question Generation Table Reasoning Datasets
Georgia Institute of Technology, Atlanta GA, USA
CRAFT: A Unified Counterfactual Reasoning Framework for Tabular Question Answering and Fact Verification
Jun 5, 2026Chenshuo Pan, Yu Zhao, Jie Zhang +7Table Reasoning Datasets LLM Reasoning Strategies
Xingchen AGI Lab,China Telecom Artificial Intelligence Technology (Beijing) Co., Ltd
Synthetic Contrastive Reasoning for Multi-Table Q&A
Jun 3, 2026Ankit Pratap Singh, Xin Su, Phillip HowardTable Reasoning Datasets Question
Iowa State University · Thoughtworks
DeliChess: A Multi-party Dialogue Dataset for Deliberation in Chess Puzzle Solving
Jun 3, 2026Xiaochen Zhu, Georgi Karadzhov, Tom Stafford +1Chess Deliberation
University of Cambridge · University of Sheffield
A Primer in Post-Training Reasoning Data: What We Know About How It Works
Jun 1, 2026Yaoming Li, Guangxiang Zhao, Qilong Shi +3Table Reasoning Datasets Post-Training
State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University · Qiyuan Tech · Tsinghua University
nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving
May 29, 2026Zhiyu Huang, Johnson Liu, Rui Song +13Naturalistic Driving Data Autonomous Driving
Xuewei · University of California, Los Angeles · 2Motional
Tailoring the Curriculum: Student-Centered Reasoning Distillation via Dynamic Data-Model Compatibility
May 28, 2026Jiahao Huang, Fei Cheng, Junfeng Jiang +1Table Reasoning Datasets Curriculum
University of Tokyo · Kyoto University · National Institute of Informatics
Error as a Lens: Probing LLM Reasoning through Synthetic Misconception Generation
May 27, 2026Xinming Yang, Jun LiStudent Misconceptions Synthetic Data
CUNY Graduate Center · CUNY Queens College
Extending Embodied Question Answering from Perception to Decision
May 25, 2026Xicheng Gong, Qiwei Li, Peiran Xu +1Embodied Table Reasoning Datasets
Peking University
MindLoom: Composing Thought Modes for Frontier-Level Reasoning Data Synthesis
May 20, 2026Haiyang Shen, Taian Guo, Xuanzhong Chen +11Table Reasoning Datasets Thoughts
1Peking University · 2Tsinghua University
Efficient Table QA via TableGrid Navigation and Progressive Inference Prompting
May 18, 2026Amritansh Maurya, Navjot Singh, Mohammed Javed +1Tabular Data Table Reasoning Datasets
Vision Intelligence Lab, IIIT Allahabad, Prayagraj, India · iMeDIA Lab, IIIT Allahabad, Prayagraj, India · CV:HCI Lab, Karlsruhe Institute of Technology, Karlsruhe, Germany
What properties of reasoning supervision are associated with improved downstream model quality?
May 13, 2026Mikołaj Langner, Dzmitry Pihulski, Jan Eliasz +5Table Reasoning Datasets Downstream Fine-Tuning
Wroclaw Tech, 50-370 Wrocław, Poland
Knowledge Distillation for Low-Resource Open-source Text-to-SQL Model
May 13, 2026Tianhao Qiu, Xiaojun ChenText-To-Sql Table Reasoning Datasets
Shenzhen University Shenzhen, China
CommonWhy: A Dataset for Evaluating Entity-Based Causal Commonsense Reasoning in Large Language Models
May 13, 2026Armin Toroghi, Faeze Moradi Kalarde, Scott SannerTable Reasoning Datasets Knowledge Graphs
University of Toronto · Toronto, ON, Canada
Can Language Models Analyze Data? Evaluating Large Language Models for Question Answering over Datasets
May 11, 2026Andreas Xenofontos, Pavlos FafaliosTable Reasoning Datasets Natural Language Datasets
School of Production Engineering and Management, Technical University of Crete, Greece · Institute of Computer Science, Foundation for Research and Technology - Hellas, Greece.
RelAgent: LLM Agents as Data Scientists for Relational Learning
May 8, 2026Xingyue Huang, Louis Tichelman, Jinwoo Kim +2Relational Deep Learning Data Science Agents
University of Oxford · AITHYRA · TU Wien +1
From 0-Order Selection to 2-Order Judgment: Combinatorial Hardening Exposes Compositional Failures in Frontier LLMs
May 8, 2026Hanmeng Liu, Shichao Weng, Xiulai Liu +3Table Reasoning Datasets Item Response Theory
Hainan University, Haikou, China · Fudan University, Shanghai, China
Anatomy of a Query: W5H Dimensions and FAR Patterns for Text-to-SQL Evaluation
May 7, 2026Vicki Stover Hertzberg, Eduardo Valverde, Joyce C. HoText-To-Sql Queries
Emory University · Georgia Institute of Technology, Atlanta, USA
StressEval: Failure-Driven Dynamic Benchmarking for Knowledge-Intensive Reasoning in Large Language Models
May 3, 2026Yongrui Chen, Yangyang Ma, Xiaoying Huang +4Stress Testing Table Reasoning Datasets
Southeast University · Hangzhou Dianzi University · Zhejiang University +1
DiagramNet: An End-to-End Recognition Framework and Dataset for Non-Standard System-Level Diagrams
May 2, 2026Jincheng Lou, Ruohan Xu, Jiapeng Li +6Diagrams Table Reasoning Datasets
School of IC, Peking University, Beijing, China · College of Artificial Intelligence, Xi’an Jiaotong University, Xi’an, China · Department of Precision Instruments, Tsinghua University, Beijing, China +4
DIAGRAMS: A Review Framework for Reasoning-Level Attribution in Diagram QA
Apr 29, 2026Anirudh Iyengar Kaniyar Narayana Iyengar, Tampu Ravi Kumar, Manan Suri +4Diagrams Reasoning Graphs
Arizona State University · University of Maryland · IIITDM +1
Generalizing Numerical Reasoning in Table Data through Operation Sketches and Self-Supervised Learning
Apr 23, 2026Hanjun Cho, Gahyun Yoo, Hanseong Kim +1Table Reasoning Datasets Supervised Finetuning
Seoul National University · Soongsil University
SemanticAgent: A Semantics-Aware Framework for Text-to-SQL Data Synthesis
Apr 23, 2026Qiang Gao, Zhenping Li, Anqi Zhuo +3Text-To-Sql Table Reasoning Datasets
Center of Information Research, Academy of Military Science, Beijing 100142, China · School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China
Post-training is (Massive) Supervised Learning
Apr 20, 2026Michael Hassid, Yossi Adi, Roy SchwartzPost-Training Pretraining
1FAIR, Meta AI · 2The Hebrew University of Jerusalem
Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards
Apr 20, 2026Raffaele Pisano, Roberto NavigliProcess Reward Model Table Reasoning Datasets
Babelscape · Sapienza University of Rome
Bridging the Reasoning Gap in Vietnamese with Small Language Models via Test-Time Scaling
Apr 20, 2026Bui The Trung, Do Minh Duc, Nguyen Van Vinh +1Small Large Language Models LLM Reasoning Strategies
Computer Science and Engineering VNU Vietnam Japan University Hanoi, Vietnam · Information Science JAIST Ishikawa, Japan · Faculty of Information VNU University of Engineering and Technology Hanoi, Vietnam +1
MERGE: Minimal Expression-Replacement GEneralization Test for Natural Language Inference
Oct 28, 2025Mădălina Zgreabăn, Tejaswini Deoskar, Lasha AbzianidzeTable Reasoning Datasets Natural Language Inference
Utrecht Institute of Linguistics OTS, Utrecht University, The Netherlands
CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes
Apr 1, 2024Paritosh Parmar, Eric Peh, Ruirui Chen +4Causal Reasoning Long Video Question Answering
Institute of High-Performance Computing, Agency for Science, Technology and Research, Singapore · Nanyang Technological University · National University of Singapore +1
Beyond Interestingness: Semantic and Context-Aware Natural Language Query Recommendations for Visual Data Analysis
Jan 13, 2022Xingbo Wang, Siyuan Li, Furui Cheng +5Relevance Table Reasoning Datasets
Bosch Research North America & Bosch Center for Artificial Intelligence (BCAI), Sunnyvale, CA, USA · Department of Computer Science and Engineering, The Hong Kong University of Science and Technology (HKUST), Hong Kong, Hong Kong, China · Dalian University of Technology, Dalian, Liaoning, China +3

Sep 12, 2026, cs.HCJ/K move · Enter open · S save

How AI Coders Discuss, Disagree, and Reach Consensus: Challenges and Opportunities for LLM-Based Qualitative Coding

Jeongyeon Kim, John Mitchell

Stanford University, Stanford, CA, USA

Qualitative Research Coding Agents Multi-Agent Large Language Model Systems Disagreement Table Reasoning Datasets Challenges

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The utility of AI in multi-coder qualitative coding has been widely discussed, yet little empirical evidence exists to delineate the contexts in which it performs reliably. We address this gap by quantifying the effectiveness of multi-agent LLM coding across varied qualitative datasets, revealing key contextual and structural factors that mediate coding outcomes. We developed a literature-informed baseline pipeline that enables AI agents to independently code, debate, and reconcile disagreements. Results revealed that coding accuracy depends on factors such as codebook length, qualitative data similarity, and agent disagreement. Notably, intense and unresolved debates between agents led to higher accuracy. Our analysis showed that while LLMs emulate many human discussion behaviors, they lack adaptive responsiveness to context. From these findings, we offer design recommendations for building automated coding systems. Our open-source AI discussion dataset and methodological framework lay the groundwork for advancing the design of AI-mediated automated thematic analysis.

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