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Machine Learning

A branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.

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Generate and Pray: Using SALLMS to Evaluate the Security of LLM Generated Code

Generate and Pray: Using SALLMS to Evaluate the Security of LLM Generated Code

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4 min read
Certifiably Robust RAG against Retrieval Corruption

Certifiably Robust RAG against Retrieval Corruption

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4 min read
Recapping the AI, Machine Learning and Data Science Meetup - May 30, 2024

Recapping the AI, Machine Learning and Data Science Meetup - May 30, 2024

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6 min read
On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models

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4 min read
YouTube Video Transcripts Using LangChain

YouTube Video Transcripts Using LangChain

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2 min read
Faithful Logical Reasoning via Symbolic Chain-of-Thought

Faithful Logical Reasoning via Symbolic Chain-of-Thought

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3 min read
An Introduction to Vision-Language Modeling

An Introduction to Vision-Language Modeling

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4 min read
Context Injection Attacks on Large Language Models

Context Injection Attacks on Large Language Models

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4 min read
Laboratory-Scale AI: Open-Weight Models are Competitive with ChatGPT Even in Low-Resource Settings

Laboratory-Scale AI: Open-Weight Models are Competitive with ChatGPT Even in Low-Resource Settings

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3 min read
Contextual Position Encoding: Learning to Count What's Important

Contextual Position Encoding: Learning to Count What's Important

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4 min read
Relightable Gaussian Codec Avatars

Relightable Gaussian Codec Avatars

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4 min read
Training-Free Long-Context Scaling of Large Language Models

Training-Free Long-Context Scaling of Large Language Models

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4 min read
Oil & Water? Diffusion of AI Within and Across Scientific Fields

Oil & Water? Diffusion of AI Within and Across Scientific Fields

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3 min read
The Impacts of Data, Ordering, and Intrinsic Dimensionality on Recall in Hierarchical Navigable Small Worlds

The Impacts of Data, Ordering, and Intrinsic Dimensionality on Recall in Hierarchical Navigable Small Worlds

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4 min read
Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks

Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks

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5 min read
Grokfast: Accelerated Grokking by Amplifying Slow Gradients

Grokfast: Accelerated Grokking by Amplifying Slow Gradients

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4 min read
Compressed-Language Models for Understanding Compressed File Formats: a JPEG Exploration

Compressed-Language Models for Understanding Compressed File Formats: a JPEG Exploration

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5 min read
Kotlin ML Pack: Technical Report

Kotlin ML Pack: Technical Report

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4 min read
Is Complexity an Illusion?

Is Complexity an Illusion?

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2 min read
Easy Problems That LLMs Get Wrong

Easy Problems That LLMs Get Wrong

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3 min read
LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning

LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning

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4 min read
BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B

BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B

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4 min read
The rising costs of training frontier AI models

The rising costs of training frontier AI models

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5 min read
Human vs. Machine: Behavioral Differences Between Expert Humans and Language Models in Wargame Simulations

Human vs. Machine: Behavioral Differences Between Expert Humans and Language Models in Wargame Simulations

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4 min read
AnyLoss: Transforming Classification Metrics into Loss Functions

AnyLoss: Transforming Classification Metrics into Loss Functions

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4 min read
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