activity
20222024
most citedPOEM: Out-of-Distribution Detection with Posterior Sampling

16 citations · 34 across the 9 of their papers we have counts for

collaborators

9 papers

cs.HC2024

Equivalence: An analysis of artists' roles with Image Generative AI from Conceptual Art perspective through an interactive installation design practice

Yixuan Li, Dan C. Baciu, Marcos Novak +1

Over the past year, the emergence of advanced text-to-image Generative AI models has significantly impacted the art world, challenging traditional notions of creativity and the rol…

cs.CL2024

ARGS: Alignment as Reward-Guided Search

Maxim Khanov, Jirayu Burapacheep, Yixuan Li

Aligning large language models with human objectives is paramount, yet common approaches including RLHF suffer from unstable and resource-intensive training. In response to this ch…

cs.LG20238 cited

Dream the Impossible: Outlier Imagination with Diffusion Models

Xuefeng Du, Yiyou Sun, Xiaojin Zhu +1

Utilizing auxiliary outlier datasets to regularize the machine learning model has demonstrated promise for out-of-distribution (OOD) detection and safe prediction. Due to the labor…

cs.LG20232 cited

When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis

Yiyou Sun, Zhenmei Shi, Yingyu Liang +1

Novel Class Discovery (NCD) aims at inferring novel classes in an unlabeled set by leveraging prior knowledge from a labeled set with known classes. Despite its importance, there i…

cs.CL20232 cited

Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection

Rheeya Uppaal, Junjie Hu, Yixuan Li

Out-of-distribution (OOD) detection is a critical task for reliable predictions over text. Fine-tuning with pre-trained language models has been a de facto procedure to derive OOD…

cs.LG2023

Distributionally Robust Optimization with Probabilistic Group

Soumya Suvra Ghosal, Yixuan Li

Modern machine learning models may be susceptible to learning spurious correlations that hold on average but not for the atypical group of samples. To address the problem, previous…