A Practitioner's Guide to Continual Multimodal Pretraining
Fuente:
arXiv
Saved in:
| Main Authors: | Roth, Karsten, Udandarao, Vishaal, Dziadzio, Sebastian, Prabhu, Ameya, Cherti, Mehdi, Vinyals, Oriol, Hénaff, Olivier, Albanie, Samuel, Bethge, Matthias, Akata, Zeynep |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
How to Merge Your Multimodal Models Over Time?
by: Dziadzio, Sebastian, et al.
Published: (2024)
by: Dziadzio, Sebastian, et al.
Published: (2024)
ONEBench to Test Them All: Sample-Level Benchmarking Over Open-Ended Capabilities
by: Ghosh, Adhiraj, et al.
Published: (2024)
by: Ghosh, Adhiraj, et al.
Published: (2024)
A Good CREPE needs more than just Sugar: Investigating Biases in Compositional Vision-Language Benchmarks
by: Udandarao, Vishaal, et al.
Published: (2025)
by: Udandarao, Vishaal, et al.
Published: (2025)
Reflecting on the State of Rehearsal-free Continual Learning with Pretrained Models
by: Thede, Lukas, et al.
Published: (2024)
by: Thede, Lukas, et al.
Published: (2024)
A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility
by: Hochlehnert, Andreas, et al.
Published: (2025)
by: Hochlehnert, Andreas, et al.
Published: (2025)
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance
by: Udandarao, Vishaal, et al.
Published: (2024)
by: Udandarao, Vishaal, et al.
Published: (2024)
Efficient Lifelong Model Evaluation in an Era of Rapid Progress
by: Prabhu, Ameya, et al.
Published: (2024)
by: Prabhu, Ameya, et al.
Published: (2024)
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model
by: Roth, Karsten, et al.
Published: (2023)
by: Roth, Karsten, et al.
Published: (2023)
Context-Aware Multimodal Pretraining
by: Roth, Karsten, et al.
Published: (2024)
by: Roth, Karsten, et al.
Published: (2024)
CiteME: Can Language Models Accurately Cite Scientific Claims?
by: Press, Ori, et al.
Published: (2024)
by: Press, Ori, et al.
Published: (2024)
Solving Spatial Supersensing Without Spatial Supersensing
by: Udandarao, Vishaal, et al.
Published: (2025)
by: Udandarao, Vishaal, et al.
Published: (2025)
Concept-Aware Batch Sampling Improves Language-Image Pretraining
by: Ghosh, Adhiraj, et al.
Published: (2025)
by: Ghosh, Adhiraj, et al.
Published: (2025)
WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs
by: Thede, Lukas, et al.
Published: (2025)
by: Thede, Lukas, et al.
Published: (2025)
Active Data Curation Effectively Distills Large-Scale Multimodal Models
by: Udandarao, Vishaal, et al.
Published: (2024)
by: Udandarao, Vishaal, et al.
Published: (2024)
Round-Trip Translation Reveals What Frontier Multilingual Benchmarks Miss
by: Skorobogat, Ronald, et al.
Published: (2026)
by: Skorobogat, Ronald, et al.
Published: (2026)
ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections
by: Bini, Massimo, et al.
Published: (2024)
by: Bini, Massimo, et al.
Published: (2024)
Dissecting Multimodal In-Context Learning: Modality Asymmetries and Circuit Dynamics in modern Transformers
by: Huang, Yiran, et al.
Published: (2026)
by: Huang, Yiran, et al.
Published: (2026)
Mapping Post-Training Forgetting in Language Models at Scale
by: Harmon, Jackson, et al.
Published: (2025)
by: Harmon, Jackson, et al.
Published: (2025)
Vision-by-Language for Training-Free Compositional Image Retrieval
by: Karthik, Shyamgopal, et al.
Published: (2023)
by: Karthik, Shyamgopal, et al.
Published: (2023)
Wu's Method can Boost Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometry
by: Sinha, Shiven, et al.
Published: (2024)
by: Sinha, Shiven, et al.
Published: (2024)
Are We Done with Object-Centric Learning?
by: Rubinstein, Alexander, et al.
Published: (2025)
by: Rubinstein, Alexander, et al.
Published: (2025)
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models
by: Singhi, Nishad, et al.
Published: (2024)
by: Singhi, Nishad, et al.
Published: (2024)
ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization
by: Eyring, Luca, et al.
Published: (2024)
by: Eyring, Luca, et al.
Published: (2024)
LLM generation novelty through the lens of semantic similarity
by: Davydov, Philipp, et al.
Published: (2025)
by: Davydov, Philipp, et al.
Published: (2025)
Infinite dSprites for Disentangled Continual Learning: Separating Memory Edits from Generalization
by: Dziadzio, Sebastian, et al.
Published: (2023)
by: Dziadzio, Sebastian, et al.
Published: (2023)
Personalizing Text-to-Image Generation to Individual Taste
by: Maerten, Anne-Sofie, et al.
Published: (2026)
by: Maerten, Anne-Sofie, et al.
Published: (2026)
Investigating Continual Pretraining in Large Language Models: Insights and Implications
by: Yıldız, Çağatay, et al.
Published: (2024)
by: Yıldız, Çağatay, et al.
Published: (2024)
Pretraining Frequency Predicts Compositional Generalization of CLIP on Real-World Tasks
by: Wiedemer, Thaddäus, et al.
Published: (2025)
by: Wiedemer, Thaddäus, et al.
Published: (2025)
Disentangled Representation Learning with the Gromov-Monge Gap
by: Uscidda, Théo, et al.
Published: (2024)
by: Uscidda, Théo, et al.
Published: (2024)
kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies
by: Gui, Zhongrui, et al.
Published: (2024)
by: Gui, Zhongrui, et al.
Published: (2024)
GRAB: A Challenging GRaph Analysis Benchmark for Large Multimodal Models
by: Roberts, Jonathan, et al.
Published: (2024)
by: Roberts, Jonathan, et al.
Published: (2024)
VGGSounder: Audio-Visual Evaluations for Foundation Models
by: Zverev, Daniil, et al.
Published: (2025)
by: Zverev, Daniil, et al.
Published: (2025)
Sparse Autoencoders are Topic Models
by: Girrbach, Leander, et al.
Published: (2025)
by: Girrbach, Leander, et al.
Published: (2025)
Time Series Representations for Classification Lie Hidden in Pretrained Vision Transformers
by: Roschmann, Simon, et al.
Published: (2025)
by: Roschmann, Simon, et al.
Published: (2025)
Investigating Structural Pruning and Recovery Techniques for Compressing Multimodal Large Language Models: An Empirical Study
by: Huang, Yiran, et al.
Published: (2025)
by: Huang, Yiran, et al.
Published: (2025)
Data-Centric Lessons To Improve Speech-Language Pretraining
by: Udandarao, Vishaal, et al.
Published: (2025)
by: Udandarao, Vishaal, et al.
Published: (2025)
DeLoRA: Decoupling Angles and Strength in Low-rank Adaptation
by: Bini, Massimo, et al.
Published: (2025)
by: Bini, Massimo, et al.
Published: (2025)
APM: Evaluating Style Personalization in LLMs with Arbitrary Preference Mappings
by: Spohn, Philipp, et al.
Published: (2026)
by: Spohn, Philipp, et al.
Published: (2026)
SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation
by: Roberts, Jonathan, et al.
Published: (2024)
by: Roberts, Jonathan, et al.
Published: (2024)
Playing repeated games with Large Language Models
by: Akata, Elif, et al.
Published: (2023)
by: Akata, Elif, et al.
Published: (2023)
Similar Items
-
How to Merge Your Multimodal Models Over Time?
by: Dziadzio, Sebastian, et al.
Published: (2024) -
ONEBench to Test Them All: Sample-Level Benchmarking Over Open-Ended Capabilities
by: Ghosh, Adhiraj, et al.
Published: (2024) -
A Good CREPE needs more than just Sugar: Investigating Biases in Compositional Vision-Language Benchmarks
by: Udandarao, Vishaal, et al.
Published: (2025) -
Reflecting on the State of Rehearsal-free Continual Learning with Pretrained Models
by: Thede, Lukas, et al.
Published: (2024) -
A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility
by: Hochlehnert, Andreas, et al.
Published: (2025)