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Matching papers

LatentPress: Context Compression Beyond Text and Vision

109 upvotes · 1 SEP 2026 · Zhengze Zhou, Hejian Sang

This paper introduces LatentPress, a method to compress conversational histories and documents into a continuous memory token format that allows language models to directly read and process the context without text reconstruction. Practitioners might care about this because it could lead to faster and more efficient language model inference.

continual learningcontext compressionlanguage modelsmemory tokensrepresentation learning

Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models

55 upvotes · 27 AUG 2026 · Senqiao Yang, Chengyao Wang, Yuxin Chen et al.

This paper proposes a new approach to training Vision-Language-Action models by using a pre-trained backbone that captures generalizable visual-action knowledge from a large, diverse dataset of robot trajectories. This allows the model to perform well on new, unseen tasks without requiring a large amount of task-specific data.

vision-language-action modelscontinual learningrepresentation learningrobot learningmultimodal learning