activity
20142024
most citedMulti-task Neural Networks for QSAR Predictions

150 citations · 446 across the 16 of their papers we have counts for

collaborators
Showing cs.LGShow all

8 papers · 1 filter

cs.LG2025

Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion

Ruixiang Zhang, Shuangfei Zhai, Yizhe Zhang +4

Discrete diffusion is a promising framework for modeling and generating discrete data. In this work, we present Target Concrete Score Matching (TCSM), a novel and versatile objecti…

cs.LG20241 cited

Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP

Chen Huang, Skyler Seto, Samira Abnar +3

Large pretrained vision-language models like CLIP have shown promising generalization capability, but may struggle in specialized domains (e.g., satellite imagery) or fine-grained…

cs.LG2023

REALM: Robust Entropy Adaptive Loss Minimization for Improved Single-Sample Test-Time Adaptation

Skyler Seto, Barry-John Theobald, Federico Danieli +2

Fully-test-time adaptation (F-TTA) can mitigate performance loss due to distribution shifts between train and test data (1) without access to the training data, and (2) without kno…

cs.LG20228 cited

Position Prediction as an Effective Pretraining Strategy

Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram +7

Transformers have gained increasing popularity in a wide range of applications, including Natural Language Processing (NLP), Computer Vision and Speech Recognition, because of thei…

cs.LG20221 cited

Efficient Representation Learning via Adaptive Context Pooling

Chen Huang, Walter Talbott, Navdeep Jaitly +1

Self-attention mechanisms model long-range context by using pairwise attention between all input tokens. In doing so, they assume a fixed attention granularity defined by the indiv…

cs.LG201618 cited

Protein Secondary Structure Prediction Using Deep Multi-scale Convolutional Neural Networks and Next-Step Conditioning

Akosua Busia, Jasmine Collins, Navdeep Jaitly

Recently developed deep learning techniques have significantly improved the accuracy of various speech and image recognition systems. In this paper we adapt some of these technique…