Key papers

• Extractive Schema Linking for Text-to-SQL (2025)
  Michael Glass et al.
  3.30
• AGVBench: A Reliability-Oriented Benchmark of Data Augmentation for Vein Recognition (2026)
  Haiyang Li et al.
  2.00
• SynCity 3000: Bootstrapping Scene-Scale 3D Diffusion (2026)
  Paul Engstler et al.
  2.00
• PhyMRI-SR: Toward Physics-Aware MRI Image Super-Resolution (2026)
  Lihua Wei et al.
  2.00
• From Foundation to Application: Improving VLA Models in Practice (2026)
  Wei Wu et al.
  2.00
• SIEVE: Structure-Aware Data Selection for Imitation Learning with VLA Models (2026)
  Changti Wu et al.
  2.00
• WildCity: A Real-World City-Scale Testbed for Rendering, Simulation, and Spatial Intelligence (2026)
  Xiangyu Han et al.
  2.00
• EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs (2026)
  Jewon Yeom et al.
  1.94
• Mid-Training with Self-Generated Data Improves Reinforcement Learning in Language Models (2026)
  Aswin RRV et al.
  1.89
• Nanbeige4.1-3B: A Small General Model that Reasons, Aligns, and Acts (2026)
  Chen Yang et al.
  1.72
• RePro: Training Language Models to Faithfully Recycle the Web for Pretraining (2025)
  Zichun Yu et al.
  1.50
• Speculative Ad-hoc Querying (2025)
  Haoyu Li et al.
  1.28
• DeepPrune: Parallel Scaling without Inter-trace Redundancy (2025)
  Shangqing Tu et al.
  1.28
• ReCode: Unify Plan and Action for Universal Granularity Control (2025)
  Zhaoyang Yu et al.
  1.28
• Agent Data Protocol: Unifying Datasets for Diverse, Effective Fine-tuning of LLM Agents (2025)
  Yueqi Song et al.
  1.28
• R2R: Efficiently Navigating Divergent Reasoning Paths with Small-Large Model Token Routing (2025)
  Tianyu Fu et al.
  1.22
• Zero-shot Text-to-SQL Learning with Auxiliary Task (2019)
  Shuaichen Chang et al.
  —
• Beyond Graph Neural Networks with Lifted Relational Neural Networks (2020)
  Gustav Sourek et al.
  —
• Structure-Grounded Pretraining for Text-to-SQL (2020)
  Xiang Deng et al.
  —
• CPM: A Large-scale Generative Chinese Pre-trained Language Model (2020)
  Zhengyan Zhang et al.
  —
• Towards Neural Programming Interfaces (2020)
  Zachary C. Brown et al.
  —
• Decoupled Dialogue Modeling and Semantic Parsing for Multi-Turn Text-to-SQL (2021)
  Zhi Chen et al.
  —
• TAPEX: Table Pre-training via Learning a Neural SQL Executor (2021)
  Qian Liu and Bei Chen and Jiaqi Guo and Morteza Ziyadi and Zeqi Lin and Weizhu Chen and Jian-Guang Lou
  —
• Text-to-Table: A New Way of Information Extraction (2021)
  Xueqing Wu et al.
  —
• DB-BERT: a Database Tuning Tool that "Reads the Manual" (2021)
  Immanuel Trummer
  —
• ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation (2021)
  Shuohuan Wang et al.
  —
• Multi-Head Deep Metric Learning Using Global and Local Representations (2021)
  Mohammad K. Ebrahimpour et al.
  —
• PseudoReasoner: Leveraging Pseudo Labels for Commonsense Knowledge Base Population (2022)
  Tianqing Fang et al.
  —
• STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing (2022)
  Zefeng Cai et al.
  —
• Towards Generalizable and Robust Text-to-SQL Parsing (2022)
  Chang Gao et al.
  —
• Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing (2023)
  Jinyang Li et al.
  —
• Schema-adaptable Knowledge Graph Construction (2023)
  Hongbin Ye et al.
  —
• Wav2SQL: Direct Generalizable Speech-To-SQL Parsing (2023)
  Huadai Liu et al.
  —
• Adapt and Decompose: Efficient Generalization of Text-to-SQL via Domain Adapted Least-To-Most Prompting (2023)
  Aseem Arora et al.
  —
• AutoML-GPT: Large Language Model for AutoML (2023)
  Yun-Da Tsai et al.
  —
• DBCopilot: Natural Language Querying over Massive Databases via Schema Routing (2023)
  Tianshu Wang et al.
  —
• Data Transformation to Construct a Dataset for Generating Entity-Relationship Model from Natural Language (2023)
  Zhenwen Li et al.
  —
• TabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition (2024)
  Md Mahadi Hasan Nahid and Davood Rafiei
  —
• NormTab: Improving Symbolic Reasoning in LLMs Through Tabular Data Normalization (2024)
  Md Mahadi Hasan Nahid et al.
  —
• TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoning (2024)
  Xinyuan Lu et al.
  —
• Data-Prep-Kit: getting your data ready for LLM application development (2024)
  David Wood et al.
  —
• TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT (2023)
  Liangyu Zha et al.
  —
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models (2024)
  Zhihong Shao et al.
  —
• CodecLM: Aligning Language Models with Tailored Synthetic Data (2024)
  Zifeng Wang et al.
  —
• Pre-training Small Base LMs with Fewer Tokens (2024)
  Sunny Sanyal et al.
  —
• DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data (2024)
  Huajian Xin et al.
  —
• Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning (2024)
  Joongwon Kim et al.
  —
• Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs (2024)
  Xin Lai et al.
  —