QeRL: Beyond Efficiency -- Quantization-enhanced Reinforcement Learning for LLMs Paper • 2510.11696 • Published 29 days ago • 173
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights Paper • 2509.22944 • Published Sep 26 • 78
ACON: Optimizing Context Compression for Long-horizon LLM Agents Paper • 2510.00615 • Published Oct 1 • 32
MCPMark: A Benchmark for Stress-Testing Realistic and Comprehensive MCP Use Paper • 2509.24002 • Published Sep 28 • 170
NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings Paper • 2509.04011 • Published Sep 4 • 28
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications Paper • 2508.16279 • Published Aug 22 • 52
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs Paper • 2508.16153 • Published Aug 22 • 154
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models Paper • 2508.09834 • Published Aug 13 • 53
ComoRAG: A Cognitive-Inspired Memory-Organized RAG for Stateful Long Narrative Reasoning Paper • 2508.10419 • Published Aug 14 • 73
A Survey of Context Engineering for Large Language Models Paper • 2507.13334 • Published Jul 17 • 258
Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models Paper • 2505.04921 • Published May 8 • 185
SmolDocling: An ultra-compact vision-language model for end-to-end multi-modal document conversion Paper • 2503.11576 • Published Mar 14 • 117