SwarmEvolve uses latent space agent swarms for faster program optimization
SwarmEvolve reaches best solutions in 3-8 minutes via latent-space KV cache sharing instead of 60 minutes.
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SwarmEvolve reaches best solutions in 3-8 minutes via latent-space KV cache sharing instead of 60 minutes.
In a driving simulator the joint search beat standalone NAS, producing higher-reward policies with fewer parameters.
On NQ320K, jointly evolving SID construction and collision handling lifts Recall@1 from 55.8% to 59.3%.
LLM-guided evolutionary search finds quantum circuits that cut Toffoli and qubit costs on seven of eight tasks.
FrugalEvo pairs a costly strategy model with cheap code refinement and beats evolutionary baselines at far lower spend.
EvoDuet co-evolves web queries and solutions, raising LLM discovery scores on 21 scientific tasks.
EvoDuet co-evolves candidate solutions and web-search queries to improve LLM scientific discovery.
MILO co-evolves agent harnesses and search strategy, beating prior harnesses on Terminal-Bench, PaperBench, and DeepSWE.
Researchers introduce GRAF, a greedy framework for crowdsourcing contest self-selection, and LLMScore, an LLM-driven method that auto-designs its scoring algorithm.
QuantumEvo uses an LLM to evolve BDD variable-ordering heuristics, achieving a 70.9% tie-or-win rate on quantum circuit cost versus baseline methods.
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