Tiny-Engram uses small n-gram-indexed memory tables to bind trigger phrases to target visual identities in diffusion models while preserving compositional control from the surrounding prompt.
Retrieval-augmented generation for knowledge-intensive NLP tasks
4 Pith papers cite this work. Polarity classification is still indexing.
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ESL-Bench supplies 100 synthetic user trajectories and 10,000 queries showing database agents achieve 48-58% accuracy while memory RAG baselines reach only 30-38% on longitudinal health reasoning.
Introduces Personal VCL formalization and benchmark revealing LMM context gaps, plus an Agentic Context Bank baseline that boosts personalized visual reasoning.
HoReN is a parameter-preserving editor that wraps an MLP with a Hopfield codebook memory and scales to 50K sequential edits on ZsRE while maintaining performance above 0.93.
citing papers explorer
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Tiny-Engram: Trigger-Indexed Concept Tables for Generative Vision
Tiny-Engram uses small n-gram-indexed memory tables to bind trigger phrases to target visual identities in diffusion models while preserving compositional control from the surrounding prompt.
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ESL-Bench: An Event-Driven Synthetic Longitudinal Benchmark for Health Agents
ESL-Bench supplies 100 synthetic user trajectories and 10,000 queries showing database agents achieve 48-58% accuracy while memory RAG baselines reach only 30-38% on longitudinal health reasoning.
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Personal Visual Context Learning in Large Multimodal Models
Introduces Personal VCL formalization and benchmark revealing LMM context gaps, plus an Agentic Context Bank baseline that boosts personalized visual reasoning.
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HoReN: Normalized Hopfield Retrieval for Large-Scale Sequential Model Editing
HoReN is a parameter-preserving editor that wraps an MLP with a Hopfield codebook memory and scales to 50K sequential edits on ZsRE while maintaining performance above 0.93.