BAIR – Berkeley Artificial Intelligence Research AI news
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Identifying Interactions at Scale for LLMs
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Understanding the behavior of complex machine learning systems, particularly Large Language Models
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Information-Driven Design of Imaging Systems
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An encoder (optical system) maps objects to noiseless images, which noise corrupts into measurements. Our information estimator uses only these noisy measurements and a noise model to quantify how well measurements distinguish -
RL without TD learning
In this post, I’ll introduce a reinforcement learning (RL) algorithm based on an “alternative” paradigm: divide and conquer. Unlike traditional methods, this algorithm is not based on temporal difference (TD) learning (which has scalability challenges), and scales well to long-horizon
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What exactly does word2vec learn?
What exactly does
...word2veclearn, and how? Answering this question amounts to understanding representation learning in a minimal yet interesting language modeling task. Despite the fact thatword2vecis a well-known precursor to modern language models, for many years, -
Whole-Body Conditioned Egocentric Video Prediction
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Defending against Prompt Injection with Structured Queries (StruQ) and Preference Optimization (SecAlign)
Recent advances in Large Language Models (LLMs) enable exciting LLM-integrated applications. However, as LLMs have improved, so have the attacks against them. Prompt injection attack is listed as the #1 threat by OWASP to LLM-integrated
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Repurposing Protein Folding Models for Generation with Latent Diffusion
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PLAID is a multimodal generative model that simultaneously generates protein 1D sequence and 3D structure, by learning the latent space of protein folding -
Scaling Up Reinforcement Learning for Traffic Smoothing: A 100-AV Highway Deployment
Training Diffusion Models with Reinforcement Learning -
Virtual Personas for Language Models via an Anthology of Backstories
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We introduce Anthology, a method for conditioning LLMs to representative, consistent, and diverse virtual personas by generating and utilizing naturalistic backstories with rich details of individual values and experience. -
Linguistic Bias in ChatGPT: Language Models Reinforce Dialect Discrimination
Sample language model responses to different varieties of English and native speaker reactions.ChatGPT does amazingly well at communicating with people in English. But whose English?