{"total":74,"rows":[{"id":"2302.07842","title":"Augmented Language Models: a Survey","created":"2023-02-15","cited_by_count":403,"area":"lr"},{"id":"2209.14610","title":"Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning","created":"2022-09-29","cited_by_count":350,"area":"lr"},{"id":"2305.09645","title":"StructGPT: A General Framework for Large Language Model to Reason over Structured Data","created":"2023-05-16","cited_by_count":343,"area":"lr"},{"id":"2302.08468","title":"LEVER: Learning to Verify Language-to-Code Generation with Execution","created":"2023-02-16","cited_by_count":239,"area":"lr"},{"id":"2401.08967","title":"ReFT: Reasoning with Reinforced Fine-Tuning","created":"2024-01-17","cited_by_count":239,"area":"lr"},{"id":"2301.13808","title":"Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning","created":"2023-01-31","cited_by_count":178,"area":"lr"},{"id":"2309.05660","title":"Hypothesis Search: Inductive Reasoning with Language Models","created":"2023-09-11","cited_by_count":120,"area":"lr"},{"id":"2108.06712","title":"HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation","created":"2021-08-15","cited_by_count":118,"area":"lr"},{"id":"2210.06710","title":"Large Language Models are few(1)-shot Table Reasoners","created":"2022-10-13","cited_by_count":116,"area":"lr"},{"id":"2401.07128","title":"EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records","created":"2024-01-13","cited_by_count":78,"area":"lr"},{"id":"2310.17342","title":"ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thought","created":"2023-10-26","cited_by_count":65,"area":"lr"},{"id":"2402.05808","title":"Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning","created":"2024-02-08","cited_by_count":65,"area":"lr"},{"id":"2402.17644","title":"Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data","created":"2024-02-27","cited_by_count":63,"area":"lr"},{"id":"2503.23157","title":"Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL","created":"2025-03-29","cited_by_count":59,"area":"lr"},{"id":"2506.23719","title":"DABstep: Data Agent Benchmark for Multi-step Reasoning","created":"2025-06-30","cited_by_count":46,"area":"lr"},{"id":"2201.11473","title":"Reasoning Like Program Executors","created":"2022-01-27","cited_by_count":45,"area":"lr"},{"id":"2404.10150","title":"TabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition","created":"2024-04-15","cited_by_count":39,"area":"lr"},{"id":"2505.20315","title":"Arctic-Text2SQL-R1: Simple Rewards, Strong Reasoning in Text-to-SQL","created":"2025-05-22","cited_by_count":38,"area":"lr"},{"id":"2505.12415","title":"Table-R1: Region-based Reinforcement Learning for Table Understanding","created":"2025-05-18","cited_by_count":37,"area":"lr"},{"id":"2312.09039","title":"TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning","created":"2023-12-14","cited_by_count":32,"area":"lr"},{"id":"2210.12374","title":"ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples","created":"2022-10-22","cited_by_count":29,"area":"lr"},{"id":"2402.08259","title":"A Survey of Table Reasoning with Large Language Models","created":"2024-02-13","cited_by_count":29,"area":"lr"},{"id":"2403.08593","title":"Call Me When Necessary: LLMs can Efficiently and Faithfully Reason over Structured Environments","created":"2024-03-13","cited_by_count":27,"area":"lr"},{"id":"2403.11886","title":"QueryAgent: A Reliable and Efficient Reasoning Framework with Environmental Feedback-based Self-Correction","created":"2024-03-18","cited_by_count":27,"area":"lr"},{"id":"2309.13182","title":"Effective Distillation of Table-based Reasoning Ability from LLMs","created":"2023-09-22","cited_by_count":23,"area":"lr"},{"id":"2403.02177","title":"ProTrix: Building Models for Planning and Reasoning over Tables with Sentence Context","created":"2024-03-04","cited_by_count":23,"area":"lr"},{"id":"2205.12682","title":"TaCube: Pre-computing Data Cubes for Answering Numerical-Reasoning Questions over Tabular Data","created":"2022-05-25","cited_by_count":19,"area":"lr"},{"id":"2506.01710","title":"Reasoning-Table: Exploring Reinforcement Learning for Table Reasoning","created":"2025-06-02","cited_by_count":18,"area":"lr"},{"id":"2502.13550","title":"STaR-SQL: Self-Taught Reasoner for Text-to-SQL","created":"2025-02-19","cited_by_count":17,"area":"lr"},{"id":"2401.15328","title":"Equipping Language Models with Tool Use Capability for Tabular Data Analysis in Finance","created":"2024-01-27","cited_by_count":14,"area":"lr"},{"id":"2504.15077","title":"Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQL","created":"2025-04-21","cited_by_count":14,"area":"lr"},{"id":"2506.05587","title":"MMTU: A Massive Multi-Task Table Understanding and Reasoning Benchmark","created":"2025-06-05","cited_by_count":14,"area":"lr"},{"id":"2412.11711","title":"MiMoTable: A Multi-scale Spreadsheet Benchmark with Meta Operations for Table Reasoning","created":"2024-12-16","cited_by_count":13,"area":"lr"},{"id":"2310.01290","title":"Knowledge Crosswords: Geometric Knowledge Reasoning with Large Language Models","created":"2023-10-02","cited_by_count":11,"area":"lr"},{"id":"2507.07424","title":"Corvid: Improving Multimodal Large Language Models Towards Chain-of-Thought Reasoning","created":"2025-07-10","cited_by_count":11,"area":"lr"},{"id":"2201.05880","title":"Reasoning over Hybrid Chain for Table-and-Text Open Domain QA","created":"2022-01-15","cited_by_count":10,"area":"lr"},{"id":"2406.20060","title":"Applying RLAIF for Code Generation with API-usage in Lightweight LLMs","created":"2024-06-28","cited_by_count":10,"area":"lr"},{"id":"2501.14693","title":"Rethinking Table Instruction Tuning","created":"2025-01-24","cited_by_count":10,"area":"lr"},{"id":"2502.11656","title":"Uncovering the Impact of Chain-of-Thought Reasoning for Direct Preference Optimization: Lessons from Text-to-SQL","created":"2025-02-17","cited_by_count":9,"area":"lr"},{"id":"2506.11684","title":"MTabVQA: Evaluating Multi-Tabular Reasoning of Language Models in Visual Space","created":"2025-06-13","cited_by_count":9,"area":"lr"},{"id":"2601.17699","title":"SQL-Trail: Multi-Turn Reinforcement Learning with Interleaved Feedback for Text-to-SQL","created":"2026-01-25","cited_by_count":7,"area":"lr"},{"id":"2406.14732","title":"TTQA-RS- A break-down prompting approach for Multi-hop Table-Text Question Answering with Reasoning and Summarization","created":"2024-06-20","cited_by_count":6,"area":"lr"},{"id":"2509.07966","title":"Visual-TableQA: Open-Domain Benchmark for Reasoning over Table Images","created":"2025-09-09","cited_by_count":6,"area":"lr"},{"id":"2202.04161","title":"Logical Reasoning for Task Oriented Dialogue Systems","created":"2022-02-08","cited_by_count":5,"area":"lr"},{"id":"2310.20170","title":"DIVKNOWQA: Assessing the Reasoning Ability of LLMs via Open-Domain Question Answering over Knowledge Base and Text","created":"2023-10-31","cited_by_count":5,"area":"lr"},{"id":"2505.01636","title":"Structured Prompting and Feedback-Guided Reasoning with LLMs for Data Interpretation","created":"2025-05-03","cited_by_count":5,"area":"lr"},{"id":"2506.21575","title":"STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing","created":"2025-06-15","cited_by_count":5,"area":"lr"},{"id":"2508.19813","title":"T2R-bench: A Benchmark for Generating Article-Level Reports from Real World Industrial Tables","created":"2025-08-27","cited_by_count":5,"area":"lr"},{"id":"2510.07642","title":"Role-Conditioned Refusals: Evaluating Access Control Reasoning in Large Language Models","created":"2025-10-09","cited_by_count":5,"area":"lr"},{"id":"2409.10007","title":"SelECT-SQL: Self-correcting ensemble Chain-of-Thought for Text-to-SQL","created":"2024-09-16","cited_by_count":4,"area":"lr"},{"id":"2505.20321","title":"BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases","created":"2025-05-23","cited_by_count":4,"area":"lr"},{"id":"2505.24377","title":"LLM Inference Enhanced by External Knowledge: A Survey","created":"2025-05-30","cited_by_count":3,"area":"lr"},{"id":"2305.14682","title":"TACR: A Table-alignment-based Cell-selection and Reasoning Model for Hybrid Question-Answering","created":"2023-05-24","cited_by_count":2,"area":"lr"},{"id":"2509.07159","title":"PaVeRL-SQL: Text-to-SQL via Partial-Match Rewards and Verbal Reinforcement Learning","created":"2025-09-08","cited_by_count":2,"area":"lr"},{"id":"2509.16929","title":"K-DeCore: Facilitating Knowledge Transfer in Continual Structured Knowledge Reasoning via Knowledge Decoupling","created":"2025-09-21","cited_by_count":2,"area":"lr"},{"id":"2510.17491","title":"Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents","created":"2025-10-20","cited_by_count":2,"area":"lr"},{"id":"2512.22364","title":"Cost Trade-offs of Reasoning and Non-Reasoning Large Language Models in Text-to-SQL","created":"2025-12-26","cited_by_count":2,"area":"lr"},{"id":"2512.23366","title":"AGRO-SQL: Agentic Group-Relative Optimization with High-Fidelity Data Synthesis","created":"2025-12-29","cited_by_count":2,"area":"lr"},{"id":"2507.21924","title":"MMAT-1M: A Large Reasoning Dataset for Multimodal Agent Tuning","created":"2025-07-29","cited_by_count":1,"area":"lr"},{"id":"2508.06110","title":"PanelTR: Zero-Shot Table Reasoning Framework Through Multi-Agent Scientific Discussion","created":"2025-08-08","cited_by_count":1,"area":"lr"},{"id":"2508.17905","title":"Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning","created":"2025-08-25","cited_by_count":1,"area":"lr"},{"id":"2511.04491","title":"RUST-BENCH: Benchmarking LLM Reasoning on Unstructured Text within Structured Tables","created":"2025-11-06","cited_by_count":1,"area":"lr"},{"id":"2510.00186","title":"Thinkquel: A Model Dedicated to Text-to-dbt Using Synthetic Data and a Span-Aware Objective","created":"2025-09-30","cited_by_count":0,"area":"lr"},{"id":"2510.25310","title":"Parrot: A Training Pipeline Enhances Both Program CoT and Natural Language CoT for Reasoning","created":"2025-10-29","cited_by_count":0,"area":"lr"},{"id":"2601.05451","title":"RingSQL: Schema-Independent Synthetic Data Generation for Text-to-SQL Reinforcement Learning","created":"2026-01-09","cited_by_count":0,"area":"lr"},{"id":"2602.00543","title":"Reasoning by Commented Code for Table Question Answering","created":"2026-01-31","cited_by_count":0,"area":"lr"},{"id":"2602.12574","title":"Monte Carlo Tree Search with Reasoning Path Refinement for Small Language Models in Conversational Text-to-NoSQL","created":"2026-02-13","cited_by_count":0,"area":"lr"},{"id":"2603.05569","title":"CBR-to-SQL: Rethinking Retrieval-based Text-to-SQL using Case-based Reasoning in the Healthcare Domain","created":"2026-03-05","cited_by_count":0,"area":"lr"},{"id":"2603.08291","title":"A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to Reasoning","created":"2026-03-09","cited_by_count":0,"area":"lr"},{"id":"2603.21018","title":"DSL-R1: From SQL to DSL for Training Retrieval Agents across Structured and Unstructured Data with Reinforcement Learning","created":"2026-01-14","cited_by_count":0,"area":"lr"},{"id":"2603.26784","title":"HighlightBench: Benchmarking Markup-Driven Table Reasoning in Scientific Documents","created":"2026-03-25","cited_by_count":0,"area":"lr"},{"id":"2605.00199","title":"RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners","created":"2026-04-30","cited_by_count":0,"area":"lr"},{"id":"2606.02109","title":"BADGER: Bridging Agentic and Deterministic Evaluation for Generative Enterprise Reasoning","created":"2026-06-01","cited_by_count":0,"area":"lr"},{"id":"2608.26036","title":"Trace Integrity for LLM Data Agents: A Vision for Auditable Structured Reasoning in Real-World Systems","created":"2026-08-26","cited_by_count":0,"area":"lr"}],"next_cursor":null}