Consolidate Memories
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Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories
arXiv:2606.03979v1 Announce Type: new Abstract: The past few decades have witnessed significant advances in the design of machine learning algorithms, from early studies on task-specific shallow models to more general deep Large Language Models (LLMs). Despite showing promising results in tasks that require instant prediction or in-context learning, existing models lack the ability to continually learn and effectively transfer their temporal in-context knowledge to their long-term...
Beyond Ground Truth in K-Complex Detection: A Waveform-Based SVM Classifier and the Limits of Expert Agreement
Objective: K-complexes (KCs) are large-amplitude EEG events that represent N2 sleep stage and have been linked to sensory gating, sleep protection, and memory consolidation. Their detection remains limited by inter-rater variability in visual scoring and by the reliance of detectors on features that discard temporal information. We propose a two-stage detector that combines a rule-based candidate localization algorithm with a Support Vector Machine (SVM) classifier operating directly on the...
Thalamic Nuclei Differentially Coordinate Propagation of Cortical Slow Oscillations
Sleep slow oscillations (SOs) vary in the spatial extent of their cortical propagation, ranging from widespread Global events to spatially restricted Frontal events. These distinctions could have functional consequences for memory consolidation. It remains unknown whether individual thalamic nuclei are differentially engaged across SO propagation types, and whether thalamic activity before SO onset predicts subsequent propagation.
Resonance-driven enhancement of sleep spindles using thalamic temporal interference stimulation
Sleep spindles are hallmarks of non-rapid eye movement sleep and support memory consolidation, yet remain difficult to modulate non-invasively. Combining computational modeling and human sleep recordings, we show that thalamus-targeted temporal interference stimulation (TIS) with a 5Hz envelope increases spindle density via subthreshold resonance in thalamocortical relay neurons. Our results demonstrate a mechanistic framework for the rational design of interventions to selectively augment...
Echo-Infinity: Learning Evolving Memory for Real-Time Infinite Video Generation
Announce Type: new Abstract: We present Echo Infinity, an autoregressive (AR) framework towards real-time infinite video generation that employs a learnable evolving memory to dynamically filter, abstract, and compress any-length history at constant cost. Existing methods mainly curate memory with predefined KV-cache schedules, fixed-ratio heuristic compression, or inference-time RoPE adaptation. These designs inevitably lose historical information and amplify compounding errors due to their...
What is a ‘normal’ memory slowdown, and when should I worry?
We’ve all been there. You walk upstairs only to find yourself wondering why you bothered. You blank on an acquaintance’s name, just as you’re introducing them.
Agent Memory: Characterization and System Implications of Stateful Long-Horizon Workloads
arXiv:2606.06448v1 Announce Type: new Abstract: LLM agents are increasingly deployed on long-horizon tasks requiring sustained reasoning over extended interaction histories. Realizing this at scale requires agents to persistently store, retrieve, and update their own memory across sessions. A rich ecosystem of agent memory systems has emerged spanning flat retrieval, LLM-mediated extraction, consolidating fact stores, and agentic control flows.
MemVerse: Multimodal Memory for Lifelong Learning Agents
arXiv:2512.03627v2 Announce Type: replace Abstract: Despite rapid progress in large-scale language and vision models, AI agents still suffer from a fundamental limitation: they cannot remember. Without reliable memory, agents catastrophically forget past experiences, struggle with long-horizon reasoning, and fail to operate coherently in multimodal or interactive environments. We introduce MemVerse, a model-agnostic, plug-and-play memory framework that bridges fast parametric recall with...
SaliMory: Orchestrating Cognitive Memory for Conversational Agents
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Short videos may hinder learning by fragmenting attention and memory, study finds
June 4, 2026 feature Short videos may hinder learning by fragmenting attention and memory, study finds Ingrid Fadelli Author Stephanie Baum Scientific Editor Robert Egan Associate Editor Recent technological advances and the introduction of new digital media platforms have dramatically changed how people learn and source information about topics that interest them. Some recent studies have found that while browsing online or scrolling down social media platforms, users tend to spend under...