Yuan Cao
4 papers · Latest:
Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent
Transformers can efficiently perform in-context logistic regression through layers that mimic normalized gradient descent steps.
Gemini: A Family of Highly Capable Multimodal Models
Gemini is a new family of multimodal AI models excelling in image, audio, video, and text understanding, achieving state-of-the-art results across numerous benchmarks including human-expert level on MMLU.
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Tree of Thoughts (ToT) is a novel inference framework that enables large language models to perform strategic, multi-step problem solving by exploring multiple reasoning paths and backtracking when needed.
ReAct: Synergizing Reasoning and Acting in Language Models
ReAct is a method that interleaves reasoning and acting in language models to improve task-solving accuracy and interpretability by enabling interaction with external environments.
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