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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2510.18866
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LightMem: Lightweight and Efficient Memory-Augmented Generation
Paper • 2510.18866 • Published • 110 -
Memory Augmented Language Models through Mixture of Word Experts
Paper • 2311.10768 • Published • 19 -
Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity
Paper • 2502.13063 • Published • 72 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 155
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TradingAgents: Multi-Agents LLM Financial Trading Framework
Paper • 2412.20138 • Published • 14 -
MinerU: An Open-Source Solution for Precise Document Content Extraction
Paper • 2409.18839 • Published • 33 -
MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing
Paper • 2509.22186 • Published • 136 -
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 121
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LightMem: Lightweight and Efficient Memory-Augmented Generation
Paper • 2510.18866 • Published • 110 -
AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders
Paper • 2510.19779 • Published • 59 -
Emu3.5: Native Multimodal Models are World Learners
Paper • 2510.26583 • Published • 106
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TokDrift: When LLM Speaks in Subwords but Code Speaks in Grammar
Paper • 2510.14972 • Published • 33 -
LightMem: Lightweight and Efficient Memory-Augmented Generation
Paper • 2510.18866 • Published • 110 -
Every Attention Matters: An Efficient Hybrid Architecture for Long-Context Reasoning
Paper • 2510.19338 • Published • 114 -
The Smol Training Playbook
📚2.53kThe secrets to building world-class LLMs
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
LightMem: Lightweight and Efficient Memory-Augmented Generation
Paper • 2510.18866 • Published • 110 -
Memory Augmented Language Models through Mixture of Word Experts
Paper • 2311.10768 • Published • 19 -
Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity
Paper • 2502.13063 • Published • 72 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 155
-
TradingAgents: Multi-Agents LLM Financial Trading Framework
Paper • 2412.20138 • Published • 14 -
MinerU: An Open-Source Solution for Precise Document Content Extraction
Paper • 2409.18839 • Published • 33 -
MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing
Paper • 2509.22186 • Published • 136 -
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 121
-
LightMem: Lightweight and Efficient Memory-Augmented Generation
Paper • 2510.18866 • Published • 110 -
AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders
Paper • 2510.19779 • Published • 59 -
Emu3.5: Native Multimodal Models are World Learners
Paper • 2510.26583 • Published • 106
-
TokDrift: When LLM Speaks in Subwords but Code Speaks in Grammar
Paper • 2510.14972 • Published • 33 -
LightMem: Lightweight and Efficient Memory-Augmented Generation
Paper • 2510.18866 • Published • 110 -
Every Attention Matters: An Efficient Hybrid Architecture for Long-Context Reasoning
Paper • 2510.19338 • Published • 114 -
The Smol Training Playbook
📚2.53kThe secrets to building world-class LLMs