
A Deep Dive into Federated Learning of LLMs
Federated Learning (FL) enables privacy-preserving training of Large Language Models (LLMs) across decentralized data sources,
Federated Learning (FL) enables privacy-preserving training of Large Language Models (LLMs) across decentralized data sources,
DeepSeek-Prover-V2 combines informal reasoning and formal proof steps to solve complex theorems , achieving top
Browser-Use is an open-source Python library that lets LLM-powered agents interact with websites via natural
Chain of Draft (CoD) optimizes LLM efficiency by reducing verbosity while maintaining accuracy. It cuts
DeepSeek’s MLA reduces KV cache memory via low-rank compression and decoupled positional encoding, enabling efficient
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
AI co-scientists powered by Gemini 2.0 accelerate scientific discovery by generating and ranking hypotheses using
SWE-Lancer benchmarks AI models on 1,400+ real freelance software engineering tasks worth $1M, evaluating their
Mixture-of-Mamba enhances State Space Models for efficient multi-modal data processing across text, images, and speech.
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