Add 33 new AI4DB papers

[LumingSun]

This PR adds 33 new papers to the AI4DB paper list.

Add 33 new AI4DB papers

Papers added:

• MoDora: Tree-Based Semi-Structured Document Analysis System
• Semantic Caching for OLAP via LLM-Based Query Canonicalization
• PromCopilot: Simplifying Prometheus Metric Querying in Cloud Native Online Service Systems via Large Language Models
• LatentTune: Efficient Tuning of High Dimensional Database Parameters via Latent Representation Learning
• DIVER: A Robust Text-to-SQL System with Dynamic Interactive Value Linking and Evidence Reasoning
• A Text-to-SQL strategy based on large language models and knowledge graphs for real-world databases
• DEL4CW: Deep Expansion Learning for Cloud Workloads Prediction
• Machine learning in modern database systems: Techniques, architectures, and deployment challenges
• Arbiter: Towards joint and fine-grained index and partition tuning in analytical databases
• A universal LLM Framework for General Query Refinements
• DarijaDB: Unlocking Text-to-SQL for Arabic Dialects
• The CitizenQuery Benchmark: A Novel Dataset and Evaluation Pipeline for Measuring LLM Performance in Citizen Query Tasks
• Beyond Static Pipelines: Learning Dynamic Workflows for Text-to-SQL
• DeepPrep: An LLM-Powered Agentic System for Autonomous Data Preparation
• OCACO: an operator-level cardinality and cost joint estimator
• Semantics and Multi-Query Optimization Algorithms for the Analyze Operator
• Learned Query Optimizer in Alibaba MaxCompute: Challenges, Analysis, and Solutions
• Disentangling Ambiguity from Instability in Large Language Models: A Clinical Text-to-SQL Case Study
• Efficient Management of High-Frequency Sensor Data Streams Using a Read-Optimized Learned Index
• ST-Raptor: An Agentic System for Semi-Structured Table QA
• Detecting and Optimizing Flawed Queries in Triplestore-Based Knowledge Systems Using Reinforcement Learning: Reinforcement Learning for Secure SPARQL …
• When temporary results meet intermediate index: An optimization technique of procedural SQL query processing
• Libra: Flexible Request Partitioning and Scheduling for Serving Unbalanced and Dynamic LLM Workloads
• Towards a Hybrid Quantum-Classical Computing Framework for Database Optimization Problems in Real Time Setup
• AgentSM: Semantic Memory for Agentic Text-to-SQL
• Piece of CAKE: Adaptive Execution Engines via Microsecond-Scale Learning
• Federated AI-Driven Query Optimization for Distributed Cloud Databases
• Meta Engine: A Unified Semantic Query Engine on Heterogeneous LLM-Based Query Systems
• Encoder–decoder-based workload forecasting framework for database-as-a-service: Y. Cheng et al.
• HeaPA: Difficulty-Aware Heap Sampling and On-Policy Query Augmentation for LLM Reinforcement Learning
• iPDB--Optimizing SQL Queries with ML and LLM Predicates
• Reflective Reasoning for SQL Generation
• Predicting a future workload for scaling database processing resources for satisfying a performance objective