Co-occurring keywords · papers mentioning both
Papers
Learning What to Remember: Adaptive Probabilistic Memory Retention for Memory-Efficient Language Models
EMNLP 2025
Quantifying Logical Consistency in Transformers via Query-Key Alignment
EMNLP 2025
TAB: Transformer Attention Bottlenecks enable User Intervention and Debugging in Vision-Language Models
ICCV 2025
VADE: Visual Attention Guided Hallucination Detection and Elimination
ACL 2025
Can Transformers Capture Spatial Relations between Objects?
ICLR 2024
Exploiting Positional Bias for Query-Agnostic Generative Content in Search
ACL 2024
Eye-Tracking Features Masking Transformer Attention in Question-Answering Tasks
COLING 2024
How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation
ICLR 2024
MaGGIe: Masked Guided Gradual Human Instance Matting
CVPR 2024
Threat Behavior Textual Search by Attention Graph Isomorphism
EACL 2024
A Closer Look at Transformer Attention for Multilingual Translation
EMNLP 2023
Topological Data Analysis for Speech Processing
Interspeech 2023
Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers
ACL 2023
A Study of the Attention Abnormality in Trojaned BERTs
NAACL 2022
Every word counts: A multilingual analysis of individual human alignment with model attention
AACL 2022
GeoNeRF: Generalizing NeRF With Geometry Priors
CVPR 2022
PartGlot: Learning Shape Part Segmentation From Language Reference Games
CVPR 2022
Time-Space Transformers for Video Panoptic Segmentation
WACV 2022
Attention-based Contrastive Learning for Winograd Schemas
EMNLP 2021
Probabilistic Attention for Interactive Segmentation
NeurIPS 2021
Accurate Word Alignment Induction from Neural Machine Translation
EMNLP 2020
Unsupervised Extractive Summarization by Pre-training Hierarchical Transformers
EMNLP 2020
An Empirical Study of Spatial Attention Mechanisms in Deep Networks
ICCV 2019
Transformer Dissection: An Unified Understanding for Transformer’s Attention via the Lens of Kernel
EMNLP 2019