SEDIMA: Cross-Run Hierarchical Insight Memory for Evolutionary Search Agents
cs.NE, cs.CL
Submitted: 2026-10-01
Updated: 2026-10-01
Sources
- Qwen3-Coder-Next Technical Report
- DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
- ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution
- SE-Search: Self-Evolving Search Agent via Memory and Dense Reward
- Towards General Text Embeddings with Multi-stage Contrastive Learning
- LLM4AD: A Platform for Algorithm Design with Large Language Model
- Prism: An Evolutionary Memory Substrate for Multi-Agent Open-Ended Discovery
- AlphaEvolve: A coding agent for scientific and algorithmic discovery
- ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory
- LoongFlow: Directed Evolutionary Search via a Cognitive Plan-Execute-Summarize Paradigm
- Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
Related papers
- Evolutionary Ensemble of Agents
- Encoding and Decoding Temporal Signals with Spiking Bandpass Wavelets
- Large Language Models and Evolutionary Computation: A Critical Review of Bidirectional Interaction, Automated Algorithm Design, and Co-Adaptive Systems
- Evolutionary Architecture Search for Chlorophyll- a Prediction in Lakes using Sentinel-2
- Learning Alzheimer's Disease Signatures by bridging EEG with Spiking Neural Networks and Biophysical Simulations
- Neuromorphic Satellite Intelligence: A Formal Framework for Event-Driven Architectures, Spike-Based Algorithms, and Quantitative Energy-Accuracy Trade-offs