Stanford University
More Factual LLMs: FactTune, a method to fine-tune LLMs for factual accuracy without human feedback
Large language models sometimes generate false statements. New work makes them more likely to produce factual output.
Stanford University
116 Posts
Stanford University
More Factual LLMs: FactTune, a method to fine-tune LLMs for factual accuracy without human feedback
Large language models sometimes generate false statements. New work makes them more likely to produce factual output.
Stanford University
Cross-Species Cell Embeddings: AI enhances cell type discovery, identifies previously elusive “Norn cells”
Researchers used an AI system to identify animal cell types from gene sequences, including a cell type that conventional approaches had discovered only in the past year.
Stanford University
Cross-Species Cell Embeddings: AI enhances cell type discovery, identifies previously elusive “Norn cells”
Researchers used an AI system to identify animal cell types from gene sequences, including a cell type that conventional approaches had discovered only in the past year.
Stanford University
Cutting the Cost of Pretrained Models: FrugalGPT, a method to cut AI costs and maintain quality
Research aims to help users select large language models that minimize expenses while maintaining quality.
Stanford University
Cutting the Cost of Pretrained Models: FrugalGPT, a method to cut AI costs and maintain quality
Research aims to help users select large language models that minimize expenses while maintaining quality.
Stanford University
Learning Language by Exploration: Agent develops language skills through simulated exploration tasks
Machine learning models typically learn language by training on tasks like predicting the next word in a given text. Researchers trained a language model in a less focused, more human-like way.
Stanford University
Learning Language by Exploration: Agent develops language skills through simulated exploration tasks
Machine learning models typically learn language by training on tasks like predicting the next word in a given text. Researchers trained a language model in a less focused, more human-like way.
Stanford University
Robot, Find My Keys: A machine learning model for robots to predict the location of objects in households
Researchers proposed a way for robots to find objects in households where things get moved around. Andrey Kurenkov and colleagues at Stanford University introduced Node Edge Predictor, a model that learned to predict where objects were located in houses.
Stanford University
Robot, Find My Keys: A machine learning model for robots to predict the location of objects in households
Researchers proposed a way for robots to find objects in households where things get moved around. Andrey Kurenkov and colleagues at Stanford University introduced Node Edge Predictor, a model that learned to predict where objects were located in houses.
Stanford University
What We Know — and Don’t Know — About Foundation Models: A new Stanford index to assess the transparency of leading AI models
A new index ranks popular AI models in terms of information their developers provide about their training, architecture, and usage. Few score well.
Stanford University
What We Know — and Don’t Know — About Foundation Models: A new Stanford index to assess the transparency of leading AI models
A new index ranks popular AI models in terms of information their developers provide about their training, architecture, and usage. Few score well.
Stanford University
LLMs Get a Life: The generative agents that mimic human behavior in a simulated town
Large language models increasingly reply to prompts with a believably human response. Can they also mimic human behavior?
Stanford University
LLMs Get a Life: The generative agents that mimic human behavior in a simulated town
Large language models increasingly reply to prompts with a believably human response. Can they also mimic human behavior?
Stanford University
ChatGPT Ain’t What It Used to Be: ChatGPT's behavior change over time
It wasn’t your imagination: OpenAI’s large language models have changed. Researchers at Stanford and UC Berkeley found that the performance of GPT-4 and GPT-3.5 has drifted in recent months. In a limited selection of tasks, some prompts yielded better results than before, some worse.
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