1 citations · 1 across the 7 of their papers we have counts for
8 papers
Efficient Preconditioned Optimization Methods with Frequent Directions
Sifan Yang, Yuanyu Wan, Yibo Wang +1
Adaptive optimization methods have received considerable attention in recent years due to their strong empirical performance. However, they generally require maintaining a precondi…
From Switching to Dynamic Regret: A Simple Reduction via Unbiased Random Sequences
Yibo Wang, Wenhao Yang, Sifan Yang +3
In non-stationary online learning, dynamic regret has attracted increasing attention as a measure of how well an online learner performs against a time-varying comparator sequence.…
Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs
Yibo Wang, Hai-Long Sun, Qing-Guo Chen +4
Recently, self-play fine-tuning (SPIN) has been proposed to adapt large language models to downstream applications with scarce expert-annotated data, by iteratively generating synt…
SPACE: Noise Contrastive Estimation Stabilizes Self-Play Fine-Tuning for Large Language Models
Yibo Wang, Qing-Guo Chen, Zhao Xu +3
Self-play fine-tuning has demonstrated promising abilities in adapting large language models (LLMs) to downstream tasks with limited real-world data. The basic principle is to iter…
Discounted Online Convex Optimization: Uniform Regret Across a Continuous Interval
Wenhao Yang, Sifan Yang, Lijun Zhang
Reflecting the greater significance of recent history over the distant past in non-stationary environments, -discounted regret has been introduced in online convex optimization…
Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization
Wei Jiang, Sifan Yang, Wenhao Yang +3
This paper investigates projection-free algorithms for stochastic constrained multi-level optimization. In this context, the objective function is a nested composition of several s…
Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
Sijia Chen, Yibo Wang, Yi-Feng Wu +5
Tool-augmented large language models (LLMs) leverage tools, often in the form of APIs, to improve their reasoning capabilities on complex tasks. This enables them to act as intelli…
Universal Online Convex Optimization with Projection per Round
Wenhao Yang, Yibo Wang, Peng Zhao +1
To address the uncertainty in function types, recent progress in online convex optimization (OCO) has spurred the development of universal algorithms that simultaneously attain min…