By combining fine-tuning and in-context learning, you get LLMs that can learn tasks that would be too...
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Mem0’s architecture is designed to LLM memory and enhance consistency for more reliable agent performance in long...
d1 framework changes boosts diffusion LLMs with novel reinforcement learning, unlocking efficient, problem-solving AI possibilities.Read More
Researchers from MIT, Yale, McGill University and others found that adapting the Sequential Monte Carlo algorithm can...
Training LLMs on trajectories of reasoning and tool use makes them superior at multi-step reasoning tasks.Read More
Not all AI scaling strategies are equal. Longer reasoning chains are not sign of higher intelligence. More...
DeepCoder-14B competes with frontier models like o3 and o1—and the weights, code, and optimization platform are open...
Reward models holding back AI? DeepSeek’s SPCT creates self-guiding critiques, promising more scalable intelligence for enterprise LLMs.Read...
While DeepSeek R1 and OpenAI o1 edge out Behemoth on a couple metrics, Llama 4 Behemoth remains...
CoTools uses hidden states and in-context learning to enable LLMs to use more than 1,000 tools very...
