57 citations · 147 across the 34 of their papers we have counts for
14 papers · 1 filter
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models
Sungik Choi, Hankook Lee, Honglak Lee +1
Novelty detection is a fundamental task of machine learning which aims to detect abnormal ( out-of-distribution (OOD)) samples. Since diffusion models have recently…
Code Models are Zero-shot Precondition Reasoners
Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu +5
One of the fundamental skills required for an agent acting in an environment to complete tasks is the ability to understand what actions are plausible at any given point. This work…
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning
Zheyuan Zhang, Shane Storks, Fengyuan Hu +4
Pre-trained language models (PLMs) have shown impressive performance in various language tasks. However, they are prone to spurious correlations, and often generate illusory inform…
Merging Generated and Retrieved Knowledge for Open-Domain QA
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran +3
Open-domain question answering (QA) systems are often built with retrieval modules. However, retrieving passages from a given source is known to suffer from insufficient knowledge…
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning
Sungjun Cho, Seunghyuk Cho, Sungwoo Park +3
Real-world graphs naturally exhibit hierarchical or cyclical structures that are unfit for the typical Euclidean space. While there exist graph neural networks that leverage hyperb…
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation
Sungjun Cho, Dae-Woong Jeong, Sung Moon Ko +5
Pretraining molecular representations from large unlabeled data is essential for molecular property prediction due to the high cost of obtaining ground-truth labels. While there ex…