Tag: AI reasoning
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Llama-3.1-8B Uses Base-10 Addition for Cyclic Reasoning
Discover how Llama-3.1-8B language model uses base-10 addition and Fourier features to reason about cyclic concepts like months.
System 1 Thinking in Large Reasoning Models Explained
Discover how large reasoning models perform fast, intuitive system 1 thinking and the challenges they face in accuracy and efficiency.
E-mem: Enhancing LLM Memory with Multi-Agent Episodic Context
Discover E-mem, a multi-agent framework improving LLM agent memory via episodic context reconstruction for superior reasoning and efficiency.
G-reasoner: Unified Reasoning with Graph & Language Models
Discover G-reasoner, a scalable framework combining graph and language models to enhance reasoning over graph-structured knowledge efficiently.
How Task Phrasing Affects Presumptions in Large Language Models
Explore how task phrasing influences presumptions in large language models, impacting their accuracy and adaptability in AI applications.