most citedUnderstanding LLM Embeddings for Regression

2 citations · 3 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2025

Towards Robust Mathematical Reasoning

Thang Luong, Dawsen Hwang, Hoang H. Nguyen +17

Finding the right north-star metrics is highly critical for advancing the mathematical reasoning capabilities of foundation models, especially given that existing evaluations are e…

cs.CL2025

Regression Language Models for Code

Yash Akhauri, Xingyou Song, Arissa Wongpanich +2

We study code-to-metric regression: predicting numeric outcomes of code executions, a challenging task due to the open-ended nature of programming languages. While prior methods ha…

cs.LG2025★ 1 cited

Performance Prediction for Large Systems via Text-to-Text Regression

Yash Akhauri, Bryan Lewandowski, Cheng-Hsi Lin +7

In many industries, predicting metric outcomes of large systems is a fundamental problem, driven largely by traditional tabular regression. However, such methods struggle on comple…

cs.LG2025

Decoding-based Regression

Xingyou Song, Dara Bahri

Language models have recently been shown capable of performing regression wherein numeric predictions are represented as decoded strings. In this work, we provide theoretical groun…

cs.LG2024★ 2 cited

Understanding LLM Embeddings for Regression

Eric Tang, Bangding Yang, Xingyou Song

With the rise of large language models (LLMs) for flexibly processing information as strings, a natural application is regression, specifically by preprocessing string representati…

cs.LG2024

Language Model Embeddings Can Be Sufficient for Bayesian Optimization

Tung Nguyen, Qiuyi Zhang, Bangding Yang +6

Bayesian Optimization is ubiquitous in experimental design and black-box optimization for improving search efficiency. However, most existing approaches rely on regression models w…

cs.LG2024

The Vizier Gaussian Process Bandit Algorithm

Xingyou Song, Qiuyi Zhang, Chansoo Lee +8

Google Vizier has performed millions of optimizations and accelerated numerous research and production systems at Google, demonstrating the success of Bayesian optimization as a la…

cs.LG2024

Position: Leverage Foundational Models for Black-Box Optimization

Xingyou Song, Yingtao Tian, Robert Tjarko Lange +3

Undeniably, Large Language Models (LLMs) have stirred an extraordinary wave of innovation in the machine learning research domain, resulting in substantial impact across diverse fi…