{"total":29,"rows":[{"id":"2405.03547","title":"Position: Leverage Foundational Models for Black-Box Optimization","created":"2024-05-06","cited_by_count":21,"area":null},{"id":"2411.14708","title":"Understanding LLM Embeddings for Regression","created":"2024-11-22","cited_by_count":19,"area":null},{"id":"2503.17286","title":"Offline Model-Based Optimization: Comprehensive Review","created":"2025-03-21","cited_by_count":15,"area":null},{"id":"2402.17423","title":"Reinforced In-Context Black-Box Optimization","created":"2024-02-27","cited_by_count":14,"area":null},{"id":"2506.21718","title":"Performance Prediction for Large Systems via Text-to-Text Regression","created":"2025-06-26","cited_by_count":14,"area":null},{"id":"2501.19383","title":"Decoding-based Regression","created":"2025-01-31","cited_by_count":12,"area":null},{"id":"2509.26476","title":"Regression Language Models for Code","created":"2025-09-30","cited_by_count":11,"area":null},{"id":"2505.01595","title":"Always Tell Me The Odds: Fine-grained Conditional Probability Estimation","created":"2025-05-02","cited_by_count":9,"area":null},{"id":"2410.10190","title":"Language Model Embeddings Can Be Sufficient for Bayesian Optimization","created":"2024-10-14","cited_by_count":8,"area":null},{"id":"2506.07109","title":"Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings","created":"2025-06-08","cited_by_count":7,"area":null},{"id":"2404.07452","title":"RiskLabs: Predicting Financial Risk Using Large Language Model based on Multimodal and Multi-Sources Data","created":"2024-04-11","cited_by_count":6,"area":null},{"id":"2403.13537","title":"What explains the success of cross-modal fine-tuning with ORCA?","created":"2024-03-20","cited_by_count":2,"area":null},{"id":"2506.08462","title":"Hybrid Reasoning for Perception, Explanation, and Autonomous Action in Manufacturing","created":"2025-06-10","cited_by_count":2,"area":null},{"id":"2507.00439","title":"Improving the Distributional Alignment of LLMs using Supervision","created":"2025-07-01","cited_by_count":2,"area":null},{"id":"2509.03244","title":"FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization","created":"2025-09-03","cited_by_count":2,"area":null},{"id":"2509.20645","title":"Anticipatory Evaluation of Language Models: Predicting LLM Benchmark Scores from Descriptions","created":"2025-09-25","cited_by_count":2,"area":null},{"id":"2510.15691","title":"Exploring the Synergy of Quantitative Factors and Newsflow Representations from Large Language Models for Stock Return Prediction","created":"2025-10-17","cited_by_count":2,"area":null},{"id":"2510.25701","title":"Interpreting LLMs as Credit Risk Classifiers: Do Their Feature Explanations Align with Classical ML?","created":"2025-10-29","cited_by_count":2,"area":null},{"id":"2602.10300","title":"Configuration-to-Performance Scaling Law with Neural Ansatz","created":"2026-02-10","cited_by_count":2,"area":null},{"id":"2603.11679","title":"LLMs can construct powerful representations and streamline sample-efficient supervised learning","created":"2026-03-12","cited_by_count":2,"area":null},{"id":"2604.01206","title":"RELISH: LLM REgression with a Latent Iterative State Head","created":"2026-04-01","cited_by_count":2,"area":null},{"id":"2405.19653","title":"SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems","created":"2024-05-30","cited_by_count":1,"area":null},{"id":"2510.03051","title":"ZeroShotOpt: Towards Zero-Shot Pretrained Models for Efficient Black-Box Optimization","created":"2025-10-03","cited_by_count":1,"area":null},{"id":"2605.11246","title":"Support-Proximity Augmented Diffusion Estimation for Offline Black-Box Optimization","created":"2026-05-11","cited_by_count":1,"area":null},{"id":"2605.20740","title":"Reinforcement Learning over Predictive Distributions for LLM Regression","created":"2026-05-20","cited_by_count":1,"area":null},{"id":"2409.05325","title":"Sample-Efficient Bayesian Optimization with Transfer Learning for Heterogeneous Search Spaces","created":"2024-09-09","cited_by_count":0,"area":null},{"id":"2504.18785","title":"ALF: Advertiser Large Foundation Model for Multi-Modal Advertiser Understanding","created":"2025-04-26","cited_by_count":0,"area":null},{"id":"2512.19701","title":"LASER: Language Model Regression for Semi-Structured Workflow Resource and Runtime Estimation","created":"2025-12-08","cited_by_count":0,"area":null},{"id":"2608.28980","title":"The Illusion of Replacement: Rethinking Specialized Machine Learning Models in the Foundation Model Era","created":"2026-08-29","cited_by_count":0,"area":null}],"next_cursor":null}