Heng Cui

Compressing LLM embeddings by 50% without sacrificing performance is now achievable by reorganizing the feature space with a learned spectral basis.

Eureka's innovative orchestration of Meta-Agents not only completes complex scientific tasks flawlessly but also uncovers new insights in quantum theory and the Riemann Hypothesis.

Filtering out high-frequency tokens from LLM embeddings can significantly enhance their semantic quality and downstream performance.