65 citations · 128 across the 12 of their papers we have counts for
12 papers
See it to Place it: Evolving Macro Placements with Vision-Language Models
Ikechukwu Uchendu, Swati Goel, Karly Hou +5
We propose using Vision-Language Models (VLMs) for macro placement in chip floorplanning, a complex optimization task that has recently shown promising advancements through machine…
Reliable Fine-Grained Evaluation of Natural Language Math Proofs
Wenjie Ma, Andrei Cojocaru, Neel Kolhe +6
Recent advances in large language models (LLMs) for mathematical reasoning have largely focused on tasks with easily verifiable final answers while generating and verifying natural…
Motion Control of High-Dimensional Musculoskeletal Systems with Hierarchical Model-Based Planning
Yunyue Wei, Shanning Zhuang, Vincent Zhuang +1
Controlling high-dimensional nonlinear systems, such as those found in biological and robotic applications, is challenging due to large state and action spaces. While deep reinforc…
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
Yunyue Wei, Vincent Zhuang, Saraswati Soedarmadji +1
Bayesian optimization is an effective technique for black-box optimization, but its applicability is typically limited to low-dimensional and small-budget problems due to the cubic…
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
Yinlam Chow, Guy Tennenholtz, Izzeddin Gur +7
Recent studies have indicated that effectively utilizing inference-time compute is crucial for attaining better performance from large language models (LLMs). In this work, we prop…
Training Language Models to Self-Correct via Reinforcement Learning
Aviral Kumar, Vincent Zhuang, Rishabh Agarwal +15
Self-correction is a highly desirable capability of large language models (LLMs), yet it has consistently been found to be largely ineffective in modern LLMs. Current methods for t…
Learning to Learn Faster from Human Feedback with Language Model Predictive Control
Jacky Liang, Fei Xia, Wenhao Yu +47
Large language models (LLMs) have been shown to exhibit a wide range of capabilities, such as writing robot code from language commands -- enabling non-experts to direct robot beha…
Kepler: Robust Learning for Faster Parametric Query Optimization
Lyric Doshi, Vincent Zhuang, Gaurav Jain +5
Most existing parametric query optimization (PQO) techniques rely on traditional query optimizer cost models, which are often inaccurate and result in suboptimal query performance.…
Barkour: Benchmarking Animal-level Agility with Quadruped Robots
Ken Caluwaerts, Atil Iscen, J. Chase Kew +41
Animals have evolved various agile locomotion strategies, such as sprinting, leaping, and jumping. There is a growing interest in developing legged robots that move like their biol…
No-Regret Reinforcement Learning with Heavy-Tailed Rewards
Vincent Zhuang, Yanan Sui
Reinforcement learning algorithms typically assume rewards to be sampled from light-tailed distributions, such as Gaussian or bounded. However, a wide variety of real-world systems…
Stagewise Safe Bayesian Optimization with Gaussian Processes
Yanan Sui, Vincent Zhuang, Joel W. Burdick +1
Enforcing safety is a key aspect of many problems pertaining to sequential decision making under uncertainty, which require the decisions made at every step to be both informative…
Multi-dueling Bandits with Dependent Arms
Yanan Sui, Vincent Zhuang, Joel W. Burdick +1
The dueling bandits problem is an online learning framework for learning from pairwise preference feedback, and is particularly well-suited for modeling settings that elicit subjec…