
Mastering Multi-Head Latent Attention
DeepSeek’s MLA reduces KV cache memory via low-rank compression and decoupled positional encoding, enabling efficient long-context processing.
DeepSeek’s MLA reduces KV cache memory via low-rank compression and decoupled positional encoding, enabling efficient long-context processing.
OpenAI’s Agents SDK enables efficient multi-agent workflows with context, tools, handoffs, and monitoring.
Portkey enables observability and tracing in multi-modal, multi-agent systems for enhanced understanding and development.
PydanticAI Agents leverage Pydantic’s validation to build reliable, type-safe AI decision-making systems.
Nexus is a lightweight Python framework for building scalable, reusable LLM-based multi-agent systems.
DRAMA enhances dense retrieval by leveraging LLM-based data augmentation and pruning to create efficient, high-performance retrievers with multilingual and long-context capabilities.
AI co-scientists powered by Gemini 2.0 accelerate scientific discovery by generating and ranking hypotheses using a multi-agent system.
SWE-Lancer benchmarks AI models on 1,400+ real freelance software engineering tasks worth $1M, evaluating their coding and management capabilities in full-stack development.
Mixture-of-Mamba enhances State Space Models for efficient multi-modal data processing across text, images, and speech.
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