Papers with transferable representations

3 papers
Representation Potentials of Foundation Models for Multimodal Alignment: A Survey (2025.emnlp-main)

Copied to clipboard

Challenge: foundation models learn highly transferable representations through large-scale pretraining on diverse data.
Approach: They examine the representation potentials of foundation models by examining their latent capacity to capture task-specific information within a single modality while providing a transferable basis for alignment and unification across modalities.
Outcome: The foundation models exhibit remarkable similarities across architectures and modalities, the authors show . the models can capture task-specific information within a single modality while providing a transferable basis for alignment and unification across modality.
MAPLE: A Meta-learning Framework for Cross-Prompt Essay Scoring (2026.findings-acl)

Copied to clipboard

Challenge: Current approaches to automate essay scoring (AES) treat each writing task as a separate task, resulting in inconsistent performance.
Approach: They propose a meta-learning framework that leverages prototypical networks to learn transferable representations across different writing prompts.
Outcome: The proposed framework outperforms baseline models on ELLIPSE and ASAP (English) and LAILA (Arabic) on three diverse datasets.
Revisiting Audio-language Pretraining for Learning General-purpose Audio Representation (2026.acl-long)

Copied to clipboard

Challenge: Existing methods for learning general-purpose audio representations are limited in scope and coverage of audio attributes.
Approach: They propose to use a 10.7M caption dataset to compare ALP with captioning . they find that contrastive learning yields competitive, transferable representations .
Outcome: The proposed model yields competitive, transferable representations, while captioning exhibits better scalability.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations